Triple

T458698
Position Surface form Disambiguated ID Type / Status
Subject Mexico Time Zones E7287 entity
Predicate includesRegion P285 FINISHED
Object Tabasco
Tabasco is a southeastern Mexican state along the Gulf of Mexico, known for its tropical climate, petroleum industry, and rich wetlands.
 E57708 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: Tabasco | Statement: [Mexico Time Zones, includesRegion, Tabasco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tabasco
Context triple: [Mexico Time Zones, includesRegion, Tabasco]
  • A. Cholula
    Cholula is a historic Mexican city famed for its Great Pyramid and rich pre-Hispanic and colonial heritage.
  • B. Canela
    Canela is a coastal rural municipality in Chile’s Coquimbo Region, known for its small agricultural communities and semi-arid landscapes.
  • C. Sinaloa
    Sinaloa is a state in northwestern Mexico known for its fertile agricultural lands, Pacific coastline, and significant role in the country's cultural and economic life.
  • D. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • E. Tecate
    Tecate is a Mexican border city in the state of Baja California, known for its brewery and as a quieter alternative crossing point near Tijuana.
  • 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: Tabasco
Triple: [Mexico Time Zones, includesRegion, Tabasco]
Generated description
Tabasco is a southeastern Mexican state along the Gulf of Mexico, known for its tropical climate, petroleum industry, and rich wetlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tabasco
Target entity description: Tabasco is a southeastern Mexican state along the Gulf of Mexico, known for its tropical climate, petroleum industry, and rich wetlands.
  • A. Cholula
    Cholula is a historic Mexican city famed for its Great Pyramid and rich pre-Hispanic and colonial heritage.
  • B. Canela
    Canela is a coastal rural municipality in Chile’s Coquimbo Region, known for its small agricultural communities and semi-arid landscapes.
  • C. Sinaloa
    Sinaloa is a state in northwestern Mexico known for its fertile agricultural lands, Pacific coastline, and significant role in the country's cultural and economic life.
  • D. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • E. Tecate
    Tecate is a Mexican border city in the state of Baja California, known for its brewery and as a quieter alternative crossing point near Tijuana.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efa4a6208190a8243a0e14f84f52 completed Feb. 28, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44f583ea081908d92fe5b5dc4d3c0 completed March 1, 2026, 2:38 p.m.
NEDg Description generation batch_69a45150b3f8819094519329a68fb1b8 completed March 1, 2026, 2:46 p.m.
NED2 Entity disambiguation (via description) batch_69a451ab785c8190b4cab0d162b4efa8 completed March 1, 2026, 2:48 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.