Triple

T13908540
Position Surface form Disambiguated ID Type / Status
Subject Province of Cuenca E334423 entity
Predicate hasMunicipality P847 FINISHED
Object Tarancón
Tarancón is a historic market town and important transport hub in central Spain’s Castilla-La Mancha region.
E1122824 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: Tarancón | Statement: [Province of Cuenca, hasMunicipality, Tarancón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarancón
Context triple: [Province of Cuenca, hasMunicipality, Tarancón]
  • A. Ayamonte
    Ayamonte is a Spanish border town in the province of Huelva, Andalusia, situated at the mouth of the Guadiana River opposite Portugal.
  • B. Caseres
    Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
  • C. Calahorra
    Calahorra is a historic city in northern Spain known for its Roman heritage and role as an agricultural and commercial center in the region of La Rioja.
  • D. Alquézar
    Alquézar is a historic hilltop village in northeastern Spain renowned for its medieval architecture and dramatic setting above the Vero River canyon.
  • E. Almendralejo
    Almendralejo is a town in the Spanish region of Extremadura known for its wine production and agricultural economy.
  • 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: Tarancón
Triple: [Province of Cuenca, hasMunicipality, Tarancón]
Generated description
Tarancón is a historic market town and important transport hub in central Spain’s Castilla-La Mancha region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tarancón
Target entity description: Tarancón is a historic market town and important transport hub in central Spain’s Castilla-La Mancha region.
  • A. Ayamonte
    Ayamonte is a Spanish border town in the province of Huelva, Andalusia, situated at the mouth of the Guadiana River opposite Portugal.
  • B. Caseres
    Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
  • C. Calahorra
    Calahorra is a historic city in northern Spain known for its Roman heritage and role as an agricultural and commercial center in the region of La Rioja.
  • D. Alquézar
    Alquézar is a historic hilltop village in northeastern Spain renowned for its medieval architecture and dramatic setting above the Vero River canyon.
  • E. Almendralejo
    Almendralejo is a town in the Spanish region of Extremadura known for its wine production and agricultural economy.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2721ec6c8190888f4a9d004eb8e0 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe387c02108190badf9b5051cd9c7a completed May 8, 2026, 7:24 p.m.
NEDg Description generation batch_69fe3df36364819081a7275b2ac604a6 completed May 8, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_69fe3e4c9cd08190b83fd437fa96297d completed May 8, 2026, 7:49 p.m.
Created at: April 9, 2026, 10:16 p.m.