Triple

T15568021
Position Surface form Disambiguated ID Type / Status
Subject Arganil E374165 entity
Predicate contains P35 FINISHED
Object Pomares
Pomares is a small village in the municipality of Arganil in central Portugal, known for its rural setting and traditional Portuguese character.
E1165564 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: Pomares | Statement: [Arganil, contains, Pomares]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pomares
Context triple: [Arganil, contains, Pomares]
  • A. Giménez
    Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
  • B. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • C. Azaña
    Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
  • D. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • E. Balazote
    Balazote is a municipality in the province of Albacete, Spain, known for its archaeological heritage and rural Castilian-La Mancha setting.
  • 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: Pomares
Triple: [Arganil, contains, Pomares]
Generated description
Pomares is a small village in the municipality of Arganil in central Portugal, known for its rural setting and traditional Portuguese character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pomares
Target entity description: Pomares is a small village in the municipality of Arganil in central Portugal, known for its rural setting and traditional Portuguese character.
  • A. Giménez
    Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
  • B. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • C. Azaña
    Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
  • D. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • E. Balazote
    Balazote is a municipality in the province of Albacete, Spain, known for its archaeological heritage and rural Castilian-La Mancha setting.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dde90b081908284d9258d4462e3 completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4219a081909acca9f783ecd44b completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff50d54960819089491ccb580784b8 completed May 9, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_69ff5208e9a08190b4a6f4157cf3c237 completed May 9, 2026, 3:26 p.m.
Created at: April 10, 2026, 4:10 a.m.