Triple

T31033514
Position Surface form Disambiguated ID Type / Status
Subject Battle of Lincoln E790793 entity
Predicate notableParticipant P6467 FINISHED
Object Susan McSween
Susan McSween was a prominent rancher and influential figure in New Mexico history, known for her role in the aftermath of the Lincoln County War and her efforts to preserve the legacy of those involved.
E1967441 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 McSween | Statement: [Battle of Lincoln, notableParticipant, Susan McSween]
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 McSween
Triple: [Battle of Lincoln, notableParticipant, Susan McSween]
Generated description
Susan McSween was a prominent rancher and influential figure in New Mexico history, known for her role in the aftermath of the Lincoln County War and her efforts to preserve the legacy of those involved.

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_69f224c97a788190b5da1ead6038a74e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694c3e0f881909ea3548ec8ab3eaf completed May 3, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d5eec408190936ed57cc54c2780 completed June 11, 2026, 9:49 p.m.
NEDg Description generation batch_6a2b31290c388190bd7d4a9762fa82c6 completed June 11, 2026, 10:05 p.m.
NED2 Entity disambiguation (via description) batch_6a2b3232bba08190a23e64699f370fbb completed June 11, 2026, 10:09 p.m.
Created at: April 29, 2026, 8:59 p.m.