Triple

T27240505
Position Surface form Disambiguated ID Type / Status
Subject One Madison E687193 entity
Predicate alsoKnownAs P39 FINISHED
Object One Madison Park
One Madison Park is a slender luxury residential skyscraper in Manhattan, New York City, known for its modern design and high-end condominiums overlooking Madison Square Park.
 E1765350 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: One Madison Park | Statement: [One Madison, alsoKnownAs, One Madison Park]
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: One Madison Park
Triple: [One Madison, alsoKnownAs, One Madison Park]
Generated description
One Madison Park is a slender luxury residential skyscraper in Manhattan, New York City, known for its modern design and high-end condominiums overlooking Madison Square Park.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6267d1440819095cd651478334377 completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1262773dac8190bb4113ab4e9b3f82 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a127060700481909293fb3b925cb760 completed May 24, 2026, 3:28 a.m.
NED2 Entity disambiguation (via description) batch_6a1270ddaf54819094cd9645435c8b6b completed May 24, 2026, 3:30 a.m.
Created at: April 27, 2026, 10:37 a.m.