Triple

T28132630
Position Surface form Disambiguated ID Type / Status
Subject Nuevo Estadio de Los Cármenes E711105 entity
Predicate alsoKnownAs P39 FINISHED
Object Los Cármenes
Los Cármenes is a football stadium in Granada, Spain, serving as the home ground of Granada CF.
E1802076 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: Los Cármenes | Statement: [Nuevo Estadio de Los Cármenes, alsoKnownAs, Los Cármenes]
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: Los Cármenes
Triple: [Nuevo Estadio de Los Cármenes, alsoKnownAs, Los Cármenes]
Generated description
Los Cármenes is a football stadium in Granada, Spain, serving as the home ground of Granada CF.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6412c8c888190aad79df596202306 completed May 2, 2026, 6:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c93bf3048190bf08ab5364c98f25 completed May 26, 2026, 4:24 p.m.
NEDg Description generation batch_6a15cb332fb08190b5a07e8d56ff8f68 completed May 26, 2026, 4:32 p.m.
NED2 Entity disambiguation (via description) batch_6a15cbefb418819096f70195dddcda5d completed May 26, 2026, 4:35 p.m.
Created at: April 27, 2026, 9:24 p.m.