Triple

T1645031
Position Surface form Disambiguated ID Type / Status
Subject El Hierro E35560 entity
Predicate hasMunicipality P847 FINISHED
Object Frontera
Frontera is a municipality on the Canary Island of El Hierro, Spain, known for its volcanic landscapes, coastal cliffs, and rural character.
 E187541 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: Frontera | Statement: [El Hierro, hasMunicipality, Frontera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frontera
Context triple: [El Hierro, hasMunicipality, Frontera]
  • A. El Fuerte
    El Fuerte is a historic colonial town and municipality in northern Sinaloa, Mexico, known for its Spanish-era architecture and role as a gateway to the Copper Canyon.
  • B. San Felipe
    San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
  • C. Mesa del Norte
    Mesa del Norte is a high, arid plateau region in northern Mexico that forms part of the country’s broader Mexican Plateau.
  • D. Hidalgo
    Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
  • E. Salmerón
    Salmerón is a Spanish surname associated with notable figures in religion, politics, and the arts.
  • 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: Frontera
Triple: [El Hierro, hasMunicipality, Frontera]
Generated description
Frontera is a municipality on the Canary Island of El Hierro, Spain, known for its volcanic landscapes, coastal cliffs, and rural character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frontera
Target entity description: Frontera is a municipality on the Canary Island of El Hierro, Spain, known for its volcanic landscapes, coastal cliffs, and rural character.
  • A. El Fuerte
    El Fuerte is a historic colonial town and municipality in northern Sinaloa, Mexico, known for its Spanish-era architecture and role as a gateway to the Copper Canyon.
  • B. San Felipe
    San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
  • C. Mesa del Norte
    Mesa del Norte is a high, arid plateau region in northern Mexico that forms part of the country’s broader Mexican Plateau.
  • D. Hidalgo
    Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
  • E. Salmerón
    Salmerón is a Spanish surname associated with notable figures in religion, politics, and the arts.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a41e5a08190b97dd1c0b12c662a completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6818c8288190af5307384f1c8080 completed March 8, 2026, 12:14 p.m.
NEDg Description generation batch_69ad68edbd2c819090c6556966eb279a completed March 8, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_69ad69724c9c8190a2314a8f30f18f7d completed March 8, 2026, 12:20 p.m.
Created at: March 4, 2026, 7:28 p.m.