Triple

T26679287
Position Surface form Disambiguated ID Type / Status
Subject Carol Wells Paul E672559 entity
Predicate hasChild P369 FINISHED
Object Lori Paul Pyeatt
Lori Paul Pyeatt is the daughter of American politician and physician Ron Paul and his wife Carol Wells Paul.
E1846892 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: Lori Paul Pyeatt | Statement: [Carol Wells Paul, hasChild, Lori Paul Pyeatt]
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: Lori Paul Pyeatt
Triple: [Carol Wells Paul, hasChild, Lori Paul Pyeatt]
Generated description
Lori Paul Pyeatt is the daughter of American politician and physician Ron Paul and his wife Carol Wells Paul.

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_69eecda13424819092b17942c4edf722 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f617060fc8819095d063081288880d completed May 2, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f3e2f748190ae3480664af84d95 completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a2523c42870819080405feb80019d83 completed June 7, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_6a252484db5081909a9f337bb31abc2c completed June 7, 2026, 7:57 a.m.
Created at: April 27, 2026, 3:18 a.m.