Triple
T781163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jersey City |
E16498
|
entity |
| Predicate | hasTransportService |
P1737
|
FINISHED |
| Object | PATH |
E21015
|
NE FINISHED |
How this triple was built (2 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: PATH | Statement: [Jersey City, hasTransportService, PATH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PATH Context triple: [Jersey City, hasTransportService, PATH]
-
A.
PATH
chosen
PATH is a rapid transit rail system connecting Manhattan in New York City with neighboring cities in northern New Jersey.
-
B.
PA
PA is the standard two-letter U.S. Postal Service abbreviation for the state of Pennsylvania.
-
C.
MAP
MAP was the abbreviated name used for the United Kingdom’s Ministry of Aircraft Production, the World War II government department responsible for overseeing and increasing aircraft manufacturing.
-
D.
Langway
Langway is the surname of Rod Langway, a Hall of Fame National Hockey League defenseman known for his defensive prowess with the Washington Capitals.
-
E.
PAR
PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a751ea3481908a622d5255249883 |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a66d9f13308190b2fccca575e03ec1 |
completed | March 3, 2026, 5:11 a.m. |
Created at: March 1, 2026, 7:37 p.m.