Triple

T38403281
Position Surface form Disambiguated ID Type / Status
Subject Mérida, Venezuela E900955 entity
Predicate hasSportFacility P2500 FINISHED
Object Estadio Metropolitano de Mérida
Estadio Metropolitano de Mérida is a major multi-purpose football stadium in Mérida, Venezuela, known for hosting professional matches and national team games.
E2275122 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: Estadio Metropolitano de Mérida | Statement: [Mérida, Venezuela, hasSportFacility, Estadio Metropolitano de Mérida]
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: Estadio Metropolitano de Mérida
Triple: [Mérida, Venezuela, hasSportFacility, Estadio Metropolitano de Mérida]
Generated description
Estadio Metropolitano de Mérida is a major multi-purpose football stadium in Mérida, Venezuela, known for hosting professional matches and national team games.

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_69f76e6071a081909eea7a670d21420c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fccd5baeec819098200e5e45bc6e32 completed May 7, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41e015139c8190983b97753e3045f1 completed June 29, 2026, 3:01 a.m.
NEDg Description generation batch_6a41e3e6eae881909146a4c4eb93f11d completed June 29, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a41e438c6c481909d641c5c5e64238b completed June 29, 2026, 3:19 a.m.
Created at: May 3, 2026, 4:31 p.m.