Triple

T27773572
Position Surface form Disambiguated ID Type / Status
Subject Rosebank, Staten Island E699122 entity
Predicate fireService P3910 FINISHED
Object FDNY Engine Company 152
FDNY Engine Company 152 is a New York City Fire Department engine company that provides firefighting and emergency response services to the Rosebank neighborhood on Staten Island.
E1788142 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: FDNY Engine Company 152 | Statement: [Rosebank, Staten Island, fireService, FDNY Engine Company 152]
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: FDNY Engine Company 152
Triple: [Rosebank, Staten Island, fireService, FDNY Engine Company 152]
Generated description
FDNY Engine Company 152 is a New York City Fire Department engine company that provides firefighting and emergency response services to the Rosebank neighborhood on Staten Island.

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_69ef6a4b5a9081909c9111396c2be3d2 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f63798a67c8190876c47dacf89af6e completed May 2, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecbd5a308190bc56732476a508c6 completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12edc0d3ec8190b8b1c8b16884ef64 completed May 24, 2026, 12:23 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee4f57508190aa0d1832b30a9556 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 5:03 p.m.