Triple

T32442938
Position Surface form Disambiguated ID Type / Status
Subject Dempo SC E829060 entity
Predicate notablePlayer P304 FINISHED
Object Beto
Beto is a former professional footballer best known as a key attacking midfielder for Indian club Dempo SC during their successful I-League era.
E2006893 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: Beto | Statement: [Dempo SC, notablePlayer, Beto]
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: Beto
Triple: [Dempo SC, notablePlayer, Beto]
Generated description
Beto is a former professional footballer best known as a key attacking midfielder for Indian club Dempo SC during their successful I-League era.

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_69f3491d2e5c819092b1c9535beff8ec completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e3d0108190bd5ecee75e662368 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f37f23081908983f9c745f3ab55 completed June 18, 2026, 8:04 p.m.
NEDg Description generation batch_6a345212a1c48190ac58fa101c175135 completed June 18, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a345f7387508190853808812475575f completed June 18, 2026, 9:13 p.m.
Created at: May 1, 2026, 12:55 a.m.