Triple

T8947536
Position Surface form Disambiguated ID Type / Status
Subject Bilbao tram E213258 entity
Predicate hasStop P17789 FINISHED
Object Atxuri stop
Atxuri stop is a tram station in Bilbao, Spain, serving as one of the stops on the city's modern tram network.
 E768428 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: Atxuri stop | Statement: [Bilbao tram, hasStop, Atxuri stop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Atxuri stop
Context triple: [Bilbao tram, hasStop, Atxuri stop]
  • A. Henti
    Henti was a queen of the Hittite Empire, known primarily as the wife of the powerful 14th-century BCE king Suppiluliuma I.
  • B. Ponto de Parada
    Ponto de Parada is a neighborhood in the city of Recife, Brazil, known primarily as a residential area within the metropolitan region.
  • C. Halt
    Halt is the surname of Karl Ritter von Halt, a notable German sports official and International Olympic Committee member in the early to mid-20th century.
  • D. Last Stop
    Last Stop is a narrative-driven adventure video game set in modern-day London that follows the intertwined supernatural stories of three playable characters.
  • E. Stopes
    Stopes is the surname of Marie Stopes, the pioneering British birth control advocate, author, and paleobotanist.
  • 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: Atxuri stop
Triple: [Bilbao tram, hasStop, Atxuri stop]
Generated description
Atxuri stop is a tram station in Bilbao, Spain, serving as one of the stops on the city's modern tram network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Atxuri stop
Target entity description: Atxuri stop is a tram station in Bilbao, Spain, serving as one of the stops on the city's modern tram network.
  • A. Henti
    Henti was a queen of the Hittite Empire, known primarily as the wife of the powerful 14th-century BCE king Suppiluliuma I.
  • B. Ponto de Parada
    Ponto de Parada is a neighborhood in the city of Recife, Brazil, known primarily as a residential area within the metropolitan region.
  • C. Halt
    Halt is the surname of Karl Ritter von Halt, a notable German sports official and International Olympic Committee member in the early to mid-20th century.
  • D. Last Stop
    Last Stop is a narrative-driven adventure video game set in modern-day London that follows the intertwined supernatural stories of three playable characters.
  • E. Stopes
    Stopes is the surname of Marie Stopes, the pioneering British birth control advocate, author, and paleobotanist.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66deb8ec819087a9c5eddd24c08a completed April 1, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc2022e30819089ba08f494a3a66f completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc27bae88819094bcfdf10e89018b completed April 3, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_69cfc61d26fc8190817b430cb6fa9646 completed April 3, 2026, 1:52 p.m.
Created at: March 30, 2026, 6:59 p.m.