Triple

T9258046
Position Surface form Disambiguated ID Type / Status
Subject Noguera Pallaresa E222494 entity
Predicate passesNear P416 FINISHED
Object Llavorsí
Llavorsí is a small village in the Catalan Pyrenees of Spain, known as a gateway for mountain tourism and white-water rafting.
E788914 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: Llavorsí | Statement: [Noguera Pallaresa, passesNear, Llavorsí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llavorsí
Context triple: [Noguera Pallaresa, passesNear, Llavorsí]
  • A. Llaillay
    Llaillay is a Chilean town and commune in the Valparaíso Region, known for its agricultural activity and location in the Aconcagua Valley.
  • B. Letňany
    Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
  • C. Lopevi
    Lopevi is an Oceanic language of Vanuatu, traditionally spoken on Lopevi Island in the central part of the archipelago.
  • D. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • E. Lelylaan
    Lelylaan is a transport hub and railway/metro station in Amsterdam’s Nieuw-West district, connecting metro, train, tram, and bus services.
  • 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: Llavorsí
Triple: [Noguera Pallaresa, passesNear, Llavorsí]
Generated description
Llavorsí is a small village in the Catalan Pyrenees of Spain, known as a gateway for mountain tourism and white-water rafting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Llavorsí
Target entity description: Llavorsí is a small village in the Catalan Pyrenees of Spain, known as a gateway for mountain tourism and white-water rafting.
  • A. Llaillay
    Llaillay is a Chilean town and commune in the Valparaíso Region, known for its agricultural activity and location in the Aconcagua Valley.
  • B. Letňany
    Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
  • C. Lopevi
    Lopevi is an Oceanic language of Vanuatu, traditionally spoken on Lopevi Island in the central part of the archipelago.
  • D. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • E. Lelylaan
    Lelylaan is a transport hub and railway/metro station in Amsterdam’s Nieuw-West district, connecting metro, train, tram, and bus services.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd06b660448190b6bc04beff0f5512 completed April 1, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09bf225608190ade085302946dd8f completed April 4, 2026, 5:04 a.m.
NEDg Description generation batch_69d09dc3ccb08190a70e278a67249070 completed April 4, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d09e3f211c819087b9e75f0d8faf93 completed April 4, 2026, 5:14 a.m.
Created at: March 30, 2026, 7:32 p.m.