Triple

T30434386
Position Surface form Disambiguated ID Type / Status
Subject John Howard Lawson E774261 entity
Predicate spouse P13 FINISHED
Object Sue Lawson
Sue Lawson was the wife of American playwright and screenwriter John Howard Lawson, a prominent figure among the Hollywood Ten.
E1927546 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: Sue Lawson | Statement: [John Howard Lawson, spouse, Sue Lawson]
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: Sue Lawson
Triple: [John Howard Lawson, spouse, Sue Lawson]
Generated description
Sue Lawson was the wife of American playwright and screenwriter John Howard Lawson, a prominent figure among the Hollywood Ten.

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_69f22492d2a88190995ce8745d9becaa completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68693d1b481909053505550c07c9d completed May 2, 2026, 11:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2898bdb7148190a2a0c44bf0a39fcc completed June 9, 2026, 10:50 p.m.
NEDg Description generation batch_6a289935dcb88190af37e6f70c9b7fc8 completed June 9, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a2899d7d0e48190b7bf380a413e5598 completed June 9, 2026, 10:55 p.m.
Created at: April 29, 2026, 8:07 p.m.