Triple

T20725183
Position Surface form Disambiguated ID Type / Status
Subject New York City Subway G line E509414 entity
Predicate servesStation P839 FINISHED
Object Carroll Street
Carroll Street is a local subway station in Brooklyn, New York City, served by the G train and connecting the Carroll Gardens and Park Slope neighborhoods.
E1957187 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: Carroll Street | Statement: [New York City Subway G line, servesStation, Carroll Street]
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: Carroll Street
Triple: [New York City Subway G line, servesStation, Carroll Street]
Generated description
Carroll Street is a local subway station in Brooklyn, New York City, served by the G train and connecting the Carroll Gardens and Park Slope neighborhoods.

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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1e7aabc819084f9e9fd45e877fd completed April 21, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a1e014f008190a6f84a9ddd32eca7 completed June 11, 2026, 2:31 a.m.
NEDg Description generation batch_6a2a2823d8408190b62a5e80e6878daf completed June 11, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_6a2a288b41bc8190bfdc652f18191347 completed June 11, 2026, 3:16 a.m.
Created at: April 16, 2026, 12:29 p.m.