Triple

T24967224
Position Surface form Disambiguated ID Type / Status
Subject Herculez Gomez E624780 entity
Predicate notableWork P4 FINISHED
Object Futbol Americas
Futbol Americas is a soccer-focused analysis and discussion show, primarily covering North and South American football, co-hosted by former U.S. international Herculez Gomez.
E1656538 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: Futbol Americas | Statement: [Herculez Gomez, notableWork, Futbol Americas]
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: Futbol Americas
Triple: [Herculez Gomez, notableWork, Futbol Americas]
Generated description
Futbol Americas is a soccer-focused analysis and discussion show, primarily covering North and South American football, co-hosted by former U.S. international Herculez Gomez.

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_69e2ff24512481908e9a72315b8d0354 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f444d9526c81908b5ee00d062d27f7 completed May 1, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a103357811881908096663a897f6a28 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a10345c68048190a7893610c58ec54c completed May 22, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a1034f2e0b88190b296a251056bce15 completed May 22, 2026, 10:50 a.m.
Created at: April 18, 2026, 6 a.m.