Triple

T36396167
Position Surface form Disambiguated ID Type / Status
Subject Avinguda d'Arístides Maillol E896485 entity
Predicate near P350 FINISHED
Object Camp Nou metro station
Camp Nou metro station is a Barcelona Metro stop serving the area around FC Barcelona’s Camp Nou stadium, providing access for fans and visitors to the sports complex.
E2183253 NE FINISHED

How this triple was built (2 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: Camp Nou metro station | Statement: [Avinguda d'Arístides Maillol, near, Camp Nou metro station]
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: Camp Nou metro station
Triple: [Avinguda d'Arístides Maillol, near, Camp Nou metro station]
Generated description
Camp Nou metro station is a Barcelona Metro stop serving the area around FC Barcelona’s Camp Nou stadium, providing access for fans and visitors to the sports complex.

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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd11938c81908ac7da5e5095cff5 completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c401797c8190a14837b5461187f0 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c4b2bf5c819082087f442c325927 completed June 22, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39c5c24c148190b5cce41203d557a1 completed June 22, 2026, 11:31 p.m.
Created at: May 3, 2026, 4:10 p.m.