Triple

T36724614
Position Surface form Disambiguated ID Type / Status
Subject Salvador Laurel E907157 entity
Predicate spouse P13 FINISHED
Object Celia Diaz Laurel
Celia Diaz Laurel was a Filipina painter, theater actress, and cultural patron known for her contributions to the arts and her role as the wife of former Philippine Vice President Salvador Laurel.
E2291273 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: Celia Diaz Laurel | Statement: [Salvador Laurel, spouse, Celia Diaz Laurel]
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: Celia Diaz Laurel
Triple: [Salvador Laurel, spouse, Celia Diaz Laurel]
Generated description
Celia Diaz Laurel was a Filipina painter, theater actress, and cultural patron known for her contributions to the arts and her role as the wife of former Philippine Vice President Salvador Laurel.

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_69f76e746e4c8190a0d05cc6d57a643e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c89ee4448190909e545b4ce70604 completed May 3, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c42c6b3c481909e6f27497cfc3245 completed July 19, 2026, 3:21 a.m.
NEDg Description generation batch_6a5c4385b4fc819082e56f9f42c23c8d completed July 19, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_6a5c43aa23fc81909d3361209996b9ec completed July 19, 2026, 3:25 a.m.
Created at: May 3, 2026, 4:12 p.m.