Triple
T5582906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMT Fourth Avenue Line |
E146681
|
entity |
| Predicate | services |
P4690
|
FINISHED |
| Object | D |
E183002
|
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: D | Statement: [BMT Fourth Avenue Line, services, D]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: D Context triple: [BMT Fourth Avenue Line, services, D]
-
A.
D
chosen
The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
-
B.
D
D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
-
C.
D
D is the vehicle registration code used on license plates for the German city of Düsseldorf.
-
D.
D
D is the standard siglum used by scholars to designate the Codex Bezae, an important early bilingual Greek-Latin manuscript of the New Testament.
-
E.
D2
D2 is a line of the Moscow Central Diameters suburban rail system, providing cross-city commuter rail service through Moscow and its surrounding areas.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0208333f08190bf0049b6bdd280f5 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0285e7bc08190bd5a08c50679e9d9 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:37 p.m.