Triple

T34978683
Position Surface form Disambiguated ID Type / Status
Subject 1891 Chicago mayoral election E1008753 entity
Predicate hasCandidate P1221 FINISHED
Object C. V. Waite
C. V. Waite was a political figure who ran as a candidate in the 1891 Chicago mayoral election.
 E2122571 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: C. V. Waite | Statement: [1891 Chicago mayoral election, hasCandidate, C. V. Waite]
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: C. V. Waite
Triple: [1891 Chicago mayoral election, hasCandidate, C. V. Waite]
Generated description
C. V. Waite was a political figure who ran as a candidate in the 1891 Chicago mayoral election.

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_69f76dc844a48190881951fffb83d17e completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78497fd708190bf7326d68af716b0 completed May 3, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd10a12c81908d6358ff7baf28c1 completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37be82cc64819089fd248f89b0ed12 completed June 21, 2026, 10:35 a.m.
NED2 Entity disambiguation (via description) batch_6a37bf4e80f481908cc78ebfdbe32528 completed June 21, 2026, 10:39 a.m.
Created at: May 3, 2026, 4:01 p.m.