Triple

T18106335
Position Surface form Disambiguated ID Type / Status
Subject Rice v. Cayetano E433352 entity
Predicate petitioner P3132 FINISHED
Object Harold F. Rice
Harold F. Rice is a Hawaii rancher and voter who became known for challenging Hawaii’s race-based voting restrictions in the landmark U.S. Supreme Court case Rice v. Cayetano.
E2197470 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: Harold F. Rice | Statement: [Rice v. Cayetano, petitioner, Harold F. Rice]
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: Harold F. Rice
Triple: [Rice v. Cayetano, petitioner, Harold F. Rice]
Generated description
Harold F. Rice is a Hawaii rancher and voter who became known for challenging Hawaii’s race-based voting restrictions in the landmark U.S. Supreme Court case Rice v. Cayetano.

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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddba6b288190af9a5d9c32d16e98 completed April 19, 2026, 1:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c1700bbac8190973472d7d95048f0 completed June 24, 2026, 5:42 p.m.
NEDg Description generation batch_6a3c17eb1a9c81909dff2e396edbe247 completed June 24, 2026, 5:46 p.m.
NED2 Entity disambiguation (via description) batch_6a3c6c95ba308190825d5700d4b6d605 completed June 24, 2026, 11:47 p.m.
Created at: April 10, 2026, 10:28 a.m.