Triple

T10847298
Position Surface form Disambiguated ID Type / Status
Subject Tzeltal people E256045 entity
Predicate mainMunicipality P91674 FINISHED
Object Sitalá
Sitalá is a rural municipality in the Mexican state of Chiapas known for its predominantly Tzeltal Maya population and traditional indigenous culture.
 E891177 NE FINISHED

How this triple was built (4 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: Sitalá | Statement: [Tzeltal people, mainMunicipality, Sitalá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sitalá
Context triple: [Tzeltal people, mainMunicipality, Sitalá]
  • A. Arnalta
    Arnalta is a comic nurse character in Claudio Monteverdi’s opera "L'incoronazione di Poppea," known for her earthy wisdom and humorous commentary.
  • B. Trisaia
    Trisaia is an ENEA research center site in southern Italy known for its activities in energy, environmental, and nuclear technology research.
  • C. Cachagua
    Cachagua is a small coastal town in central Chile known for its beaches, upscale vacation homes, and tranquil seaside atmosphere.
  • D. Tirico
    Tirico is the surname of American sportscaster Mike Tirico, known for his play-by-play work on major sports broadcasts.
  • E. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Sitalá
Triple: [Tzeltal people, mainMunicipality, Sitalá]
Generated description
Sitalá is a rural municipality in the Mexican state of Chiapas known for its predominantly Tzeltal Maya population and traditional indigenous culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sitalá
Target entity description: Sitalá is a rural municipality in the Mexican state of Chiapas known for its predominantly Tzeltal Maya population and traditional indigenous culture.
  • A. Arnalta
    Arnalta is a comic nurse character in Claudio Monteverdi’s opera "L'incoronazione di Poppea," known for her earthy wisdom and humorous commentary.
  • B. Trisaia
    Trisaia is an ENEA research center site in southern Italy known for its activities in energy, environmental, and nuclear technology research.
  • C. Cachagua
    Cachagua is a small coastal town in central Chile known for its beaches, upscale vacation homes, and tranquil seaside atmosphere.
  • D. Tirico
    Tirico is the surname of American sportscaster Mike Tirico, known for his play-by-play work on major sports broadcasts.
  • E. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • F. None of above. chosen

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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75113bc188190ac78df0c51d95de6 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7cc0d648190afb0ce80bac7f3dc completed April 15, 2026, 8:40 p.m.
NEDg Description generation batch_69e0b498df2481908c964d53b1782774 completed April 16, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_69e11e21fc2c8190878a877ecd3b465e completed April 16, 2026, 5:36 p.m.
Created at: April 8, 2026, 9:20 p.m.