Triple

T36766627
Position Surface form Disambiguated ID Type / Status
Subject José Vasconcelos E908357 entity
Predicate birthPlace P1 FINISHED
Object Oaxaca de Juárez, Oaxaca, Mexico
Oaxaca de Juárez is the historic capital city of the Mexican state of Oaxaca, renowned for its rich indigenous culture, colonial architecture, and vibrant arts and culinary traditions.
E2198000 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: Oaxaca de Juárez, Oaxaca, Mexico | Statement: [José Vasconcelos, birthPlace, Oaxaca de Juárez, Oaxaca, Mexico]
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: Oaxaca de Juárez, Oaxaca, Mexico
Triple: [José Vasconcelos, birthPlace, Oaxaca de Juárez, Oaxaca, Mexico]
Generated description
Oaxaca de Juárez is the historic capital city of the Mexican state of Oaxaca, renowned for its rich indigenous culture, colonial architecture, and vibrant arts and culinary traditions.

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_69f76e786ba481909cdcf6cf6b39dd32 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c981240c819089bac537309067dd completed May 3, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c17457a9c8190a756a4414170ec3a completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c49aa50f4819091bc6cfe25a2b162 completed June 24, 2026, 9:18 p.m.
NED2 Entity disambiguation (via description) batch_6a3c8827b2dc8190a01730e1903020ae completed June 25, 2026, 1:45 a.m.
Created at: May 3, 2026, 4:12 p.m.