Triple

T15567586
Position Surface form Disambiguated ID Type / Status
Subject Ourém E374155 entity
Predicate contains P35 FINISHED
Object Atouguia
Atouguia is a civil parish located within the municipality of Ourém in central Portugal.
E1165495 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: Atouguia | Statement: [Ourém, contains, Atouguia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atouguia
Context triple: [Ourém, contains, Atouguia]
  • A. Waynoka
    Waynoka is a small city in northwestern Oklahoma known historically as a railroad hub and as a gateway to the nearby Little Sahara State Park sand dunes.
  • B. Amboim
    Amboim is a municipality in Angola known for its agricultural activities within the coastal Cuanza Sul Province.
  • C. Fonte Grande
    Fonte Grande is a notable historic fountain and local landmark in the village of Alte in Portugal’s Algarve region, attracting visitors for its traditional charm and scenic setting.
  • D. Araguaína
    Araguaína is a major commercial and economic center in northern Brazil, located in the state of Tocantins.
  • E. Corumbá
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • 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: Atouguia
Triple: [Ourém, contains, Atouguia]
Generated description
Atouguia is a civil parish located within the municipality of Ourém in central Portugal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Atouguia
Target entity description: Atouguia is a civil parish located within the municipality of Ourém in central Portugal.
  • A. Waynoka
    Waynoka is a small city in northwestern Oklahoma known historically as a railroad hub and as a gateway to the nearby Little Sahara State Park sand dunes.
  • B. Amboim
    Amboim is a municipality in Angola known for its agricultural activities within the coastal Cuanza Sul Province.
  • C. Fonte Grande
    Fonte Grande is a notable historic fountain and local landmark in the village of Alte in Portugal’s Algarve region, attracting visitors for its traditional charm and scenic setting.
  • D. Araguaína
    Araguaína is a major commercial and economic center in northern Brazil, located in the state of Tocantins.
  • E. Corumbá
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • 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.