Triple

T25666774
Position Surface form Disambiguated ID Type / Status
Subject Presidio County, Texas E643540 entity
Predicate contains P35 FINISHED
Object Candelaria, Texas
Candelaria, Texas is a small, remote unincorporated community on the Rio Grande along the U.S.–Mexico border in far West Texas.
E1691906 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: Candelaria, Texas | Statement: [Presidio County, Texas, contains, Candelaria, Texas]
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: Candelaria, Texas
Triple: [Presidio County, Texas, contains, Candelaria, Texas]
Generated description
Candelaria, Texas is a small, remote unincorporated community on the Rio Grande along the U.S.–Mexico border in far West Texas.

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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb2fc5d48190985fa055091b239d completed May 2, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c15536348190bff44e71cd538b54 completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c25f38548190a7487c7cb829bce0 completed May 22, 2026, 8:53 p.m.
NED2 Entity disambiguation (via description) batch_6a10c4dc54f481909f2e06eaa2d15d43 completed May 22, 2026, 9:04 p.m.
Created at: April 21, 2026, 7:06 p.m.