Triple

T10769178
Position Surface form Disambiguated ID Type / Status
Subject Vallès Oriental E254029 entity
Predicate contains P35 FINISHED
Object Vallromanes
Vallromanes is a small municipality in the province of Barcelona, Catalonia, known for its natural surroundings, golf course, and proximity to the coastal and metropolitan areas.
E884776 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: Vallromanes | Statement: [Vallès Oriental, contains, Vallromanes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vallromanes
Context triple: [Vallès Oriental, contains, Vallromanes]
  • A. Vallon
    Vallon is a small municipality in the canton of Fribourg in western Switzerland.
  • B. Famenne
    Famenne is a natural and historical region in southern Belgium characterized by its limestone landscapes, caves, and rural scenery.
  • C. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • D. Tavèrnoles
    Tavèrnoles is a small municipality in the comarca of Osona in Catalonia, northeastern Spain, known for its rural landscape and traditional Catalan character.
  • E. Fargas
    Fargas is a surname most notably associated with American actor Antonio Fargas, known for his character roles in film and television.
  • 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: Vallromanes
Triple: [Vallès Oriental, contains, Vallromanes]
Generated description
Vallromanes is a small municipality in the province of Barcelona, Catalonia, known for its natural surroundings, golf course, and proximity to the coastal and metropolitan areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vallromanes
Target entity description: Vallromanes is a small municipality in the province of Barcelona, Catalonia, known for its natural surroundings, golf course, and proximity to the coastal and metropolitan areas.
  • A. Vallon
    Vallon is a small municipality in the canton of Fribourg in western Switzerland.
  • B. Famenne
    Famenne is a natural and historical region in southern Belgium characterized by its limestone landscapes, caves, and rural scenery.
  • C. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • D. Tavèrnoles
    Tavèrnoles is a small municipality in the comarca of Osona in Catalonia, northeastern Spain, known for its rural landscape and traditional Catalan character.
  • E. Fargas
    Fargas is a surname most notably associated with American actor Antonio Fargas, known for his character roles in film and television.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7322f9968819098b0ad54b913bfe4 completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69de236d0a78819090774656b7b492e5 completed April 14, 2026, 11:22 a.m.
NEDg Description generation batch_69de271fb08c8190a44c547083226fd8 completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2cecc24c8190a240366e0600426a completed April 14, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:16 p.m.