Triple
T628268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Times Square–42nd Street subway station |
E15867
|
entity |
| Predicate | servedByService |
P1294
|
FINISHED |
| Object |
W
The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
|
E78747
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: W | Statement: [Times Square–42nd Street subway station, servedByService, W]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: W Context triple: [Times Square–42nd Street subway station, servedByService, W]
-
A.
W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
-
B.
WR
WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
-
C.
WN
WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
-
D.
WW
WW is the commonly used abbreviation for Woodsworth College, a constituent college of the University of Toronto known for its diverse student body and focus on continuing and part-time education.
-
E.
W3
W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: W Triple: [Times Square–42nd Street subway station, servedByService, W]
Generated description
The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: W Target entity description: The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
-
A.
W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
-
B.
WR
WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
-
C.
WN
WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
-
D.
WW
WW is the commonly used abbreviation for Woodsworth College, a constituent college of the University of Toronto known for its diverse student body and focus on continuing and part-time education.
-
E.
W3
W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56938be6481909a8eba01f5d856c1 |
completed | March 2, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_69a569ec60a08190ad2f84dc20635621 |
completed | March 2, 2026, 10:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a56a6d09cc8190959d8d2e7621041f |
completed | March 2, 2026, 10:46 a.m. |
Created at: March 1, 2026, 7:35 p.m.