Triple

T28032152
Position Surface form Disambiguated ID Type / Status
Subject Wayne Morris E708301 entity
Predicate spouse P13 FINISHED
Object Patricia O’Rourke
Patricia O’Rourke was the wife of American actor Wayne Morris, known primarily in relation to his Hollywood career and personal life.
E1932612 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: Patricia O’Rourke | Statement: [Wayne Morris, spouse, Patricia O’Rourke]
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: Patricia O’Rourke
Triple: [Wayne Morris, spouse, Patricia O’Rourke]
Generated description
Patricia O’Rourke was the wife of American actor Wayne Morris, known primarily in relation to his Hollywood career and personal life.

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_69ef9b6bdd9c8190bb3a574a03774ad1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63c733844819085a729181009c2b6 completed May 2, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbb59bb481908b035c7e803e0a02 completed June 10, 2026, 1:19 a.m.
NEDg Description generation batch_6a28bc2af92c8190a955710cdd763158 completed June 10, 2026, 1:21 a.m.
NED2 Entity disambiguation (via description) batch_6a28bcf1f5d081908823910cd023c991 completed June 10, 2026, 1:25 a.m.
Created at: April 27, 2026, 8:17 p.m.