Triple

T6123394
Position Surface form Disambiguated ID Type / Status
Subject Crato E136535 entity
Predicate hasMunicipalSeat P1474 FINISHED
Object Crato (urban area)
Crato (urban area) is the main town and administrative center of the municipality of Crato in Portugal.
 E572026 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: Crato (urban area) | Statement: [Crato, hasMunicipalSeat, Crato (urban area)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Crato (urban area)
Context triple: [Crato, hasMunicipalSeat, Crato (urban area)]
  • A. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • B. Lajeado
    Lajeado is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
  • C. Neiva
    Neiva is a major city in southwestern Colombia known as the economic and cultural center of the upper Magdalena River valley.
  • D. Vinhedo
    Vinhedo is a municipality in southeastern Brazil known for its high quality of life, proximity to Campinas, and attractions such as the Hopi Hari theme park and annual grape festival.
  • E. Bemposta
    Bemposta is a civil parish located within the municipality of Abrantes in central Portugal.
  • 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: Crato (urban area)
Triple: [Crato, hasMunicipalSeat, Crato (urban area)]
Generated description
Crato (urban area) is the main town and administrative center of the municipality of Crato in Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Crato (urban area)
Target entity description: Crato (urban area) is the main town and administrative center of the municipality of Crato in Portugal.
  • A. Vila Verde
    Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
  • B. Lajeado
    Lajeado is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
  • C. Neiva
    Neiva is a major city in southwestern Colombia known as the economic and cultural center of the upper Magdalena River valley.
  • D. Vinhedo
    Vinhedo is a municipality in southeastern Brazil known for its high quality of life, proximity to Campinas, and attractions such as the Hopi Hari theme park and annual grape festival.
  • E. Bemposta
    Bemposta is a civil parish located within the municipality of Abrantes in central Portugal.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05c25976081909e0a40e07dff0b8a completed March 22, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135abcef08190a899d7ba261ebb04 completed March 23, 2026, 12:44 p.m.
NEDg Description generation batch_69c13877c7148190aa4d583206a53185 completed March 23, 2026, 12:56 p.m.
NED2 Entity disambiguation (via description) batch_69c138eccd4c8190bf540f84ba6c1d65 completed March 23, 2026, 12:58 p.m.
Created at: March 22, 2026, 4:14 p.m.