Triple

T16270912
Position Surface form Disambiguated ID Type / Status
Subject Baix Ebre E394995 entity
Predicate contains P35 FINISHED
Object Camarles
Camarles is a municipality in the Baix Ebre comarca of Catalonia, Spain, known for its agricultural landscape near the Ebro Delta.
E1204216 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: Camarles | Statement: [Baix Ebre, contains, Camarles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camarles
Context triple: [Baix Ebre, contains, Camarles]
  • A. Vacqueyras
    Vacqueyras is a renowned southern Rhône wine appellation in France known for its robust red wines primarily based on Grenache, Syrah, and Mourvèdre.
  • B. Vidigueira
    Vidigueira is a municipality in Portugal’s Alentejo region, known for its wine production and historical ties to the explorer Vasco da Gama.
  • C. Sotres
    Sotres is a small mountain village in Asturias, northern Spain, known as a popular base for hiking and accessing the Picos de Europa.
  • D. Lavezares
    Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • E. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • 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: Camarles
Triple: [Baix Ebre, contains, Camarles]
Generated description
Camarles is a municipality in the Baix Ebre comarca of Catalonia, Spain, known for its agricultural landscape near the Ebro Delta.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Camarles
Target entity description: Camarles is a municipality in the Baix Ebre comarca of Catalonia, Spain, known for its agricultural landscape near the Ebro Delta.
  • A. Vacqueyras
    Vacqueyras is a renowned southern Rhône wine appellation in France known for its robust red wines primarily based on Grenache, Syrah, and Mourvèdre.
  • B. Vidigueira
    Vidigueira is a municipality in Portugal’s Alentejo region, known for its wine production and historical ties to the explorer Vasco da Gama.
  • C. Sotres
    Sotres is a small mountain village in Asturias, northern Spain, known as a popular base for hiking and accessing the Picos de Europa.
  • D. Lavezares
    Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • E. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e246099dd081908e268a1a0cf8a373 completed April 17, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017bf09888190b3d90db3517a2f1e completed May 10, 2026, 5:29 a.m.
NEDg Description generation batch_6a00193f71548190b40feeea73b0c252 completed May 10, 2026, 5:35 a.m.
NED2 Entity disambiguation (via description) batch_6a001a0def548190a1d800f858f3cb02 completed May 10, 2026, 5:39 a.m.
Created at: April 10, 2026, 5:05 a.m.