Triple
T38657774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIRR Atlantic Branch |
E939940
|
entity |
| Predicate | connectsToSubway |
P158586
|
FINISHED |
| Object | New York City Subway at Atlantic Terminal |
—
|
NE NERFINISHED |
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: New York City Subway at Atlantic Terminal | Statement: [LIRR Atlantic Branch, connectsToSubway, New York City Subway at Atlantic Terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToSubway Context triple: [LIRR Atlantic Branch, connectsToSubway, New York City Subway at Atlantic Terminal]
-
A.
hasSubway
Indicates that a place is served by or contains a subway (metro) system.
-
B.
hasSubwayCode
Indicates that an entity is associated with a specific subway system code used to identify it within that transit network.
-
C.
hasSubwaySymbol
Indicates that one entity is used as the official subway symbol or icon representing another entity.
-
D.
hasSubwayComplex
Indicates that one entity contains or is associated with a subway complex as part of its structure or facilities.
-
E.
hasOverpassOrSubway
chosen
Indicates that one location is connected to or accessible from another via an overpass or a subway passage.
- F. None of above.
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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a002962f6e081909906d6436bae6407 |
completed | May 10, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_6a00284c9c7c8190a77f18a41eee55df |
completed | May 10, 2026, 6:40 a.m. |
Created at: May 3, 2026, 4:33 p.m.