Triple
T38328475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aizoon S.L. |
E1036854
|
entity |
| Predicate | implicatedPerson |
P190792
|
FINISHED |
| Object | Iñaki Urdangarin |
—
|
NE NERFINISHED |
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: Iñaki Urdangarin | Statement: [Aizoon S.L., implicatedPerson, Iñaki Urdangarin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: implicatedPerson Context triple: [Aizoon S.L., implicatedPerson, Iñaki Urdangarin]
-
A.
involvedActor
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
B.
allegedParticipant
Indicates that an entity is claimed or suspected to have taken part in an event, action, or situation, without this participation being confirmed as fact.
-
C.
involvedOfficer
Indicates that an officer participated in, was connected to, or played a role in a particular incident, case, or event.
-
D.
closelyInvolvedWith
Indicates a relationship in which one entity is deeply and actively engaged with another’s activities, decisions, or affairs.
-
E.
allegedActor
Indicates that the subject is claimed or accused to be the actor responsible for a particular action or event, without confirming that the claim is true.
- F. None of above. chosen
Provenance (4 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fcd148e6d4819082c118832ecc599b |
completed | May 7, 2026, 5:52 p.m. |
Created at: May 3, 2026, 4:30 p.m.