Triple

T35617316
Position Surface form Disambiguated ID Type / Status
Subject Dominica Freedom Party E1029209 entity
Predicate foundedBy P104 FINISHED
Object H.L. Seignoret
H.L. Seignoret was a Dominican political figure best known as the founder of the Dominica Freedom Party.
E2149212 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: H.L. Seignoret | Statement: [Dominica Freedom Party, foundedBy, H.L. Seignoret]
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: H.L. Seignoret
Triple: [Dominica Freedom Party, foundedBy, H.L. Seignoret]
Generated description
H.L. Seignoret was a Dominican political figure best known as the founder of the Dominica Freedom Party.

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_69f76e0709408190bbe322bf1707ef6b completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79eed47d88190b1f3b273072c4002 completed May 3, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a386848ed6c819084daa8bb1f920a82 completed June 21, 2026, 10:40 p.m.
NEDg Description generation batch_6a386913196c81908274a2e909d943b8 completed June 21, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a3869ecb09c8190bffe477099dcc2cf completed June 21, 2026, 10:47 p.m.
Created at: May 3, 2026, 4:05 p.m.