Triple

T5975324
Position Surface form Disambiguated ID Type / Status
Subject Zaragoza province E132970 entity
Predicate contains P35 FINISHED
Object Daroca
Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
 E570115 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: Daroca | Statement: [Zaragoza province, contains, Daroca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daroca
Context triple: [Zaragoza province, contains, Daroca]
  • A. Calatayud
    Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
  • B. Barbastro
    Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
  • C. 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.
  • D. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • E. Lebrija
    Lebrija is a historic town and municipality in southern Spain’s Andalusia region, known for its agricultural economy and traditional flamenco culture.
  • 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: Daroca
Triple: [Zaragoza province, contains, Daroca]
Generated description
Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daroca
Target entity description: Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
  • A. Calatayud
    Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
  • B. Barbastro
    Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
  • C. 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.
  • D. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • E. Lebrija
    Lebrija is a historic town and municipality in southern Spain’s Andalusia region, known for its agricultural economy and traditional flamenco culture.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a39c9d08190a78e1e3268584eb5 completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c13557696881909b50c8b72af6878c completed March 23, 2026, 12:43 p.m.
NEDg Description generation batch_69c1362a78548190b3ccbc9089821b40 completed March 23, 2026, 12:46 p.m.
NED2 Entity disambiguation (via description) batch_69c1368d452c8190bc713c0f508250a8 completed March 23, 2026, 12:48 p.m.
Created at: March 22, 2026, 4:04 p.m.