Triple

T23965366
Position Surface form Disambiguated ID Type / Status
Subject 74th Street–Broadway (IRT Flushing Line) E604062 entity
Predicate hasAdjacentStation P231 FINISHED
Object 69th Street (IRT Flushing Line)
69th Street is a local New York City Subway station on the IRT Flushing Line in Queens, served by the 7 train.
E1610447 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: 69th Street (IRT Flushing Line) | Statement: [74th Street–Broadway (IRT Flushing Line), hasAdjacentStation, 69th Street (IRT Flushing Line)]
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: 69th Street (IRT Flushing Line)
Triple: [74th Street–Broadway (IRT Flushing Line), hasAdjacentStation, 69th Street (IRT Flushing Line)]
Generated description
69th Street is a local New York City Subway station on the IRT Flushing Line in Queens, served by the 7 train.

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_69e29543019c8190872462e593cc50b4 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d1d7077881909d4774b7040cd722 completed April 29, 2026, 9:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f765de0808190b35df63f08becf00 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f77225bec81908590adc4f49a1e1e completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78c015108190bb84972406f84239 completed May 21, 2026, 9:27 p.m.
Created at: April 17, 2026, 9:24 p.m.