Triple
T24766511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kia Sorento (PBA) |
E619597
|
entity |
| Predicate | playingCoach |
P157110
|
FINISHED |
| Object | Manny Pacquiao |
—
|
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: Manny Pacquiao | Statement: [Kia Sorento (PBA), playingCoach, Manny Pacquiao]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playingCoach Context triple: [Kia Sorento (PBA), playingCoach, Manny Pacquiao]
-
A.
gameCoached
Indicates that one entity served as the coach for another entity in the context of a specific game or match.
-
B.
coachProfession
Indicates that one entity serves professionally as a coach in relation to the other entity.
-
C.
featuredCoach
Indicates that a particular coach is highlighted or given special prominence within a specific context or collection.
-
D.
playerCoachTeam
Indicates a relationship where a player is coached by a specific coach while playing for a particular team.
-
E.
coachesSport
Indicates that one entity serves as the coach or trainer responsible for another entity’s participation in a particular sport.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a6a5d08190b8f518b3cc13a2e7 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410a001788190a457e41f53aaf90c |
completed | May 1, 2026, 2:32 a.m. |
Created at: April 18, 2026, 4:28 a.m.