Triple
T729720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Beach–JFK Airport station |
E14803
|
entity |
| Predicate | hasFreeTransfer |
P19480
|
FINISHED |
| Object | between A train platforms |
—
|
LITERAL 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: between A train platforms | Statement: [Howard Beach–JFK Airport station, hasFreeTransfer, between A train platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFreeTransfer Context triple: [Howard Beach–JFK Airport station, hasFreeTransfer, between A train platforms]
-
A.
hasTransfer
Indicates a relationship where something is moved or conveyed from one entity or location to another.
-
B.
hasFreeZone
Indicates that an entity includes or is associated with a designated free zone area where special rules, privileges, or exemptions apply.
-
C.
hasFreeEntry
Indicates that access to something (such as an event, place, or service) does not require payment of an entry fee.
-
D.
hasFreeTradeAgreement
Indicates that two entities are linked by a formal free trade agreement that reduces or eliminates trade barriers between them.
-
E.
hasRelegationTo
Indicates that an entity is demoted or moved down to a lower level, tier, or division within a hierarchical system.
- F. None of above. chosen
Provenance (4 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f9b7608190bf97c8418a26e632 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a66658948190bdae6e521951954f |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.