Triple

T33424958
Position Surface form Disambiguated ID Type / Status
Subject LDU Quito E855947 entity
Predicate notablePlayer P304 FINISHED
Object Édison Méndez
Édison Méndez is an Ecuadorian former professional footballer and midfielder renowned for his influential performances for club and country, including key roles in Ecuador’s World Cup campaigns.
E2284267 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: Édison Méndez | Statement: [LDU Quito, notablePlayer, Édison Méndez]
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: Édison Méndez
Triple: [LDU Quito, notablePlayer, Édison Méndez]
Generated description
Édison Méndez is an Ecuadorian former professional footballer and midfielder renowned for his influential performances for club and country, including key roles in Ecuador’s World Cup campaigns.

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_69f3496fdf0081908c1aa30870ce518b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e45c0e8c81909f0bfcd2ebdb1a8f completed May 3, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4329e605088190b23701fd67b034bf completed June 30, 2026, 2:28 a.m.
NEDg Description generation batch_6a4331fe687881908e2a6dfa0da7e5d7 completed June 30, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_6a433279afb481909a95a1a57c283bea completed June 30, 2026, 3:05 a.m.
Created at: May 1, 2026, 1:36 a.m.