Triple

T31363777
Position Surface form Disambiguated ID Type / Status
Subject Midtown Manhattan pedestrian network E799949 entity
Predicate integratedWith P2830 FINISHED
Object New York City Subway stations
New York City Subway stations are the extensive network of underground and elevated train stops that form the backbone of public transit across New York City’s five boroughs.
 E1958057 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: New York City Subway stations | Statement: [Midtown Manhattan pedestrian network, integratedWith, New York City Subway stations]
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: New York City Subway stations
Triple: [Midtown Manhattan pedestrian network, integratedWith, New York City Subway stations]
Generated description
New York City Subway stations are the extensive network of underground and elevated train stops that form the backbone of public transit across New York City’s five boroughs.

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_69f224e6b7448190ac6bf97ad7364160 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f82ba5c8190acc54dfa7b82ee26 completed May 3, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a72298b04819084c9a0b8f886b080 completed June 11, 2026, 8:30 a.m.
NEDg Description generation batch_6a2a7610a0f881908aa503bc8096b767 completed June 11, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2a8ea4a7008190bb00ed03315455be completed June 11, 2026, 10:32 a.m.
Created at: April 29, 2026, 9:18 p.m.