Triple

T23847576
Position Surface form Disambiguated ID Type / Status
Subject Chicano mural movement E592065 entity
Predicate notableArtist P601 FINISHED
Object Willie Herrón
Willie Herrón is a prominent Chicano artist and muralist known for his influential, politically charged public artworks and role in shaping the Chicano art movement in Los Angeles.
E1634403 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: Willie Herrón | Statement: [Chicano mural movement, notableArtist, Willie Herrón]
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: Willie Herrón
Triple: [Chicano mural movement, notableArtist, Willie Herrón]
Generated description
Willie Herrón is a prominent Chicano artist and muralist known for his influential, politically charged public artworks and role in shaping the Chicano art movement in Los Angeles.

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_69e25d221d908190b9b502ad31e66a3f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c9851f988190af39f57f9b71da03 completed April 29, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe334e06481908a0918de150bc01c completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe44e2f9c8190a16f81052341c70a completed May 22, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe4e5d698819092a5d1b75f213ca0 completed May 22, 2026, 5:08 a.m.
Created at: April 17, 2026, 8:10 p.m.