Triple

T27250619
Position Surface form Disambiguated ID Type / Status
Subject 2013 New York City mayoral election E687474 entity
Predicate thirdPartyGeneralElectionCandidate P6377 FINISHED
Object Jack Hidary
Jack Hidary is an American entrepreneur and philanthropist known for his work in technology and clean energy, as well as his independent candidacy in New York City politics.
E1800463 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: Jack Hidary | Statement: [2013 New York City mayoral election, thirdPartyGeneralElectionCandidate, Jack Hidary]
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: Jack Hidary
Triple: [2013 New York City mayoral election, thirdPartyGeneralElectionCandidate, Jack Hidary]
Generated description
Jack Hidary is an American entrepreneur and philanthropist known for his work in technology and clean energy, as well as his independent candidacy in New York City politics.

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_69ef35567e808190a94458cd44ebff0c completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6bd2f061081909798c04674844492 completed May 3, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a15b86b25088190ad6082499161f25e completed May 26, 2026, 3:12 p.m.
NEDg Description generation batch_6a15bc3f71b881909b2add9409d75b78 completed May 26, 2026, 3:29 p.m.
NED2 Entity disambiguation (via description) batch_6a15bcf711148190882bb2f6f46fd40e completed May 26, 2026, 3:32 p.m.
Created at: April 27, 2026, 10:45 a.m.