Triple

T32822934
Position Surface form Disambiguated ID Type / Status
Subject Alva Adams E839479 entity
Predicate electedIn P1239 FINISHED
Object 1896 Colorado gubernatorial election
The 1896 Colorado gubernatorial election was a state-level contest in which Democrat Alva Adams won the governorship amid the political realignments of the late 19th century.
 E2025525 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: 1896 Colorado gubernatorial election | Statement: [Alva Adams, electedIn, 1896 Colorado gubernatorial election]
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: 1896 Colorado gubernatorial election
Triple: [Alva Adams, electedIn, 1896 Colorado gubernatorial election]
Generated description
The 1896 Colorado gubernatorial election was a state-level contest in which Democrat Alva Adams won the governorship amid the political realignments of the late 19th century.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdf368008190a62d85407c004479 completed May 3, 2026, 4:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bcf426c88190ad48a08641adbed7 completed June 19, 2026, 3:52 a.m.
NEDg Description generation batch_6a34bdd9563481909fc9714f2a1872df completed June 19, 2026, 3:56 a.m.
NED2 Entity disambiguation (via description) batch_6a34bef5b65881908b336a301dc210a9 completed June 19, 2026, 4 a.m.
Created at: May 1, 2026, 1:15 a.m.