Triple

T10644899
Position Surface form Disambiguated ID Type / Status
Subject Berguedà E250811 entity
Predicate contains P35 FINISHED
Object Casserres
Casserres is a municipality in the comarca of Berguedà in Catalonia, northeastern Spain.
E878560 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: Casserres | Statement: [Berguedà, contains, Casserres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Casserres
Context triple: [Berguedà, contains, Casserres]
  • A. Lavezares
    Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • B. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • C. Serques
    Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
  • D. Espalion
    Espalion is a picturesque commune in southern France’s Aveyron department, known for its historic architecture and scenic riverside setting in the Lot Valley.
  • E. Camprodon
    Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
  • 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: Casserres
Triple: [Berguedà, contains, Casserres]
Generated description
Casserres is a municipality in the comarca of Berguedà in Catalonia, northeastern Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Casserres
Target entity description: Casserres is a municipality in the comarca of Berguedà in Catalonia, northeastern Spain.
  • A. Lavezares
    Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • B. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • C. Serques
    Serques is a small commune in the Pas-de-Calais department in northern France, situated within the administrative area of Saint-Omer.
  • D. Espalion
    Espalion is a picturesque commune in southern France’s Aveyron department, known for its historic architecture and scenic riverside setting in the Lot Valley.
  • E. Camprodon
    Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfd04ca88190ac4fffd13c1f33a8 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d988530f288190b8150d159f723a74 completed April 10, 2026, 11:31 p.m.
NEDg Description generation batch_69d98afa316c8190b9645401d8e43f59 completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98c013348819094bde38a057257b4 completed April 10, 2026, 11:47 p.m.
Created at: April 8, 2026, 9:05 p.m.