Triple

T37245539
Position Surface form Disambiguated ID Type / Status
Subject Ocosingo Municipality E923837 entity
Predicate borders P224 FINISHED
Object La Trinitaria Municipality
La Trinitaria Municipality is an administrative region in the southern Mexican state of Chiapas, known for its rural communities and proximity to the Guatemalan border.
E2219118 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: La Trinitaria Municipality | Statement: [Ocosingo Municipality, borders, La Trinitaria Municipality]
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: La Trinitaria Municipality
Triple: [Ocosingo Municipality, borders, La Trinitaria Municipality]
Generated description
La Trinitaria Municipality is an administrative region in the southern Mexican state of Chiapas, known for its rural communities and proximity to the Guatemalan border.

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_69f76eaabb4c819093b751b139dad551 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb36fb4bc8819095ed76f48e7bb8d6 completed May 6, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043cbd3648190b0e8420f961c80b7 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a4046228bf08190abeae852adcb839d completed June 27, 2026, 9:52 p.m.
NED2 Entity disambiguation (via description) batch_6a40467eab3481908a6fb5b61d742925 completed June 27, 2026, 9:54 p.m.
Created at: May 3, 2026, 4:15 p.m.