Triple
T21471344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015 FIFA corruption case |
E529738
|
entity |
| Predicate | involvesOfficial |
P134903
|
FINISHED |
| Object |
Julio Rocha
Julio Rocha was a Nicaraguan football administrator and former FIFA development officer who became widely known for his involvement in the 2015 FIFA corruption scandal.
|
E1626880
|
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: Julio Rocha | Statement: [2015 FIFA corruption case, involvesOfficial, Julio Rocha]
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: Julio Rocha Triple: [2015 FIFA corruption case, involvesOfficial, Julio Rocha]
Generated description
Julio Rocha was a Nicaraguan football administrator and former FIFA development officer who became widely known for his involvement in the 2015 FIFA corruption scandal.
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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea13adfc819093324ae6fe66c3fd |
completed | April 23, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fc98202248190a2e3ee03c4e7078a |
completed | May 22, 2026, 3:12 a.m. |
| NEDg | Description generation | batch_6a0fcade9db88190b79f8f03c9b5f51f |
completed | May 22, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fcb724a888190838a30e05e556421 |
completed | May 22, 2026, 3:20 a.m. |
Created at: April 16, 2026, 6:18 p.m.