Triple

T33509449
Position Surface form Disambiguated ID Type / Status
Subject Larry Linville E858199 entity
Predicate spouse P13 FINISHED
Object Susan Hagan
Susan Hagan is known as the spouse of American actor Larry Linville, who played Major Frank Burns on the television series M*A*S*H.
E2053106 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: Susan Hagan | Statement: [Larry Linville, spouse, Susan Hagan]
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: Susan Hagan
Triple: [Larry Linville, spouse, Susan Hagan]
Generated description
Susan Hagan is known as the spouse of American actor Larry Linville, who played Major Frank Burns on the television series M*A*S*H.

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_69f3497721848190978fbee5e0a526f8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f66d016c8190b1c7fbd797ee1274 completed May 3, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595c940188190a76b19f00cc5364d completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a359724ebd48190b7158f852f890b86 completed June 19, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_6a3598177b708190ab4da13476634995 completed June 19, 2026, 7:27 p.m.
Created at: May 1, 2026, 1:38 a.m.