Triple
T36579775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Nadal |
E902357
|
entity |
| Predicate | coachedToTitle |
P186201
|
FINISHED |
| Object | Rafael Nadal Grand Slam singles titles |
—
|
LITERAL 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: Rafael Nadal Grand Slam singles titles | Statement: [Toni Nadal, coachedToTitle, Rafael Nadal Grand Slam singles titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachedToTitle Context triple: [Toni Nadal, coachedToTitle, Rafael Nadal Grand Slam singles titles]
-
A.
coachTitle
Indicates the formal title or designation held by a coach in relation to a team, organization, or role.
-
B.
coachedFrom
Indicates that one entity served as a coach or trainer for another entity during a specified period or context.
-
C.
coachedFormat
Indicates that one entity served as a coach or trainer to another entity in a particular format, style, or structured context.
-
D.
coachedRole
Indicates that one entity served as a coach for another entity in a specific role or position.
-
E.
coachedUntil
Indicates that one entity served as a coach for another entity or team up to a specified end time or date.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7cabacc1481909e839454ce1057f7 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7c9f4c7c48190ba918d8d5dc8dfd9 |
completed | May 3, 2026, 10:19 p.m. |
Created at: May 3, 2026, 4:11 p.m.