Triple

T35620089
Position Surface form Disambiguated ID Type / Status
Subject Kat Cammack E1029286 entity
Predicate precededBy P97 FINISHED
Object Ted Yoho
Ted Yoho is an American veterinarian and Republican politician who represented Florida’s 3rd congressional district in the U.S. House of Representatives from 2013 to 2021.
E2148415 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: Ted Yoho | Statement: [Kat Cammack, precededBy, Ted Yoho]
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: Ted Yoho
Triple: [Kat Cammack, precededBy, Ted Yoho]
Generated description
Ted Yoho is an American veterinarian and Republican politician who represented Florida’s 3rd congressional district in the U.S. House of Representatives from 2013 to 2021.

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_69f79ef00064819096b8eae7f5cdd30a completed May 3, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385bf316508190ac46123d38ac9ac9 completed June 21, 2026, 9:47 p.m.
NEDg Description generation batch_6a385c8966a08190a3e50867b439b9a1 completed June 21, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a385d6d137c8190854b4078389e3016 completed June 21, 2026, 9:53 p.m.
Created at: May 3, 2026, 4:05 p.m.