Triple

T23821935
Position Surface form Disambiguated ID Type / Status
Subject Prohibition Party E589259 entity
Predicate notablePresidentialCandidate P13677 FINISHED
Object D. Leigh Colvin
D. Leigh Colvin was an American lawyer, writer, and prominent temperance advocate who became a leading figure in the Prohibition Party’s national political campaigns.
E1612581 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: D. Leigh Colvin | Statement: [Prohibition Party, notablePresidentialCandidate, D. Leigh Colvin]
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: D. Leigh Colvin
Triple: [Prohibition Party, notablePresidentialCandidate, D. Leigh Colvin]
Generated description
D. Leigh Colvin was an American lawyer, writer, and prominent temperance advocate who became a leading figure in the Prohibition Party’s national political campaigns.

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_69e25d18619081909c7fb89d8926f14a completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7afff6c819096a0af7e008ea8d4 completed April 29, 2026, 8:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e5a687c8190910e6c97fe48be87 completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7f21e3608190b646947083391923 completed May 21, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f7fc9437c8190999551269a49fb65 completed May 21, 2026, 9:57 p.m.
Created at: April 17, 2026, 7:59 p.m.