Triple

T26475196
Position Surface form Disambiguated ID Type / Status
Subject Dyer Avenue E666010 entity
Predicate connectsTo P845 FINISHED
Object West 37th Street
West 37th Street is a major east–west street in Midtown Manhattan, New York City, running through a dense mix of commercial, office, and residential buildings.
 E1815805 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: West 37th Street | Statement: [Dyer Avenue, connectsTo, West 37th 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: West 37th Street
Triple: [Dyer Avenue, connectsTo, West 37th Street]
Generated description
West 37th Street is a major east–west street in Midtown Manhattan, New York City, running through a dense mix of commercial, office, and residential buildings.

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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612cce1348190861a76259a2b9c85 completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1632d4a994819087ff83f117c7066a completed May 26, 2026, 11:55 p.m.
NEDg Description generation batch_6a163495d6888190a6c226919d78ee45 completed May 27, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_6a16353dbdf88190b6d85c1b6c0c195c completed May 27, 2026, 12:05 a.m.
Created at: April 27, 2026, 12:22 a.m.