Triple

T2566596
Position Surface form Disambiguated ID Type / Status
Subject Capiz E57364 entity
Predicate hasMunicipality P847 FINISHED
Object Pontevedra
Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
 E284986 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: Pontevedra | Statement: [Capiz, hasMunicipality, Pontevedra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pontevedra
Context triple: [Capiz, hasMunicipality, Pontevedra]
  • A. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • B. A Coruña
    A Coruña is a coastal city in northwestern Spain known for its historic lighthouse, the Tower of Hercules, and its role as an important cultural and economic center in the region.
  • C. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • D. Ourense
    Ourense is a historic inland city in northwestern Spain known for its thermal springs and Roman bridge over the Miño River.
  • E. Gijón
    Gijón is a coastal city in northern Spain’s Asturias region, known for its major seaport, maritime heritage, and beaches along the Bay of Biscay.
  • 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: Pontevedra
Triple: [Capiz, hasMunicipality, Pontevedra]
Generated description
Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pontevedra
Target entity description: Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • A. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • B. A Coruña
    A Coruña is a coastal city in northwestern Spain known for its historic lighthouse, the Tower of Hercules, and its role as an important cultural and economic center in the region.
  • C. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • D. Ourense
    Ourense is a historic inland city in northwestern Spain known for its thermal springs and Roman bridge over the Miño River.
  • E. Gijón
    Gijón is a coastal city in northern Spain’s Asturias region, known for its major seaport, maritime heritage, and beaches along the Bay of Biscay.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3602ed08190aad0f9c7ac577eb0 completed March 7, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98ab023481908ab51febe79b963c completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af9960992881909d7d4ed12630ce33 completed March 10, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69af99c394ac81908601f495b4c7b77d completed March 10, 2026, 4:10 a.m.
Created at: March 6, 2026, 9:48 p.m.