Triple
T4956982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Hildebrand |
E111305
|
entity |
| Predicate | positionPlayedOnTeamOrSpeciality |
P11751
|
FINISHED |
| Object | umpire |
—
|
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: umpire | Statement: [George Hildebrand, positionPlayedOnTeamOrSpeciality, umpire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionPlayedOnTeamOrSpeciality Context triple: [George Hildebrand, positionPlayedOnTeamOrSpeciality, umpire]
-
A.
playsInPosition
chosen
Indicates that an entity (typically a player) performs or operates in a specific role or position within a game, sport, or activity.
-
B.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
C.
teamSpecialty
Indicates the particular area of expertise or focus that characterizes a team’s skills or activities.
-
D.
clubPosition
Indicates the specific role or position an individual holds within a sports club or team.
-
E.
positionInLineup
Indicates the specific ordered place an entity occupies within a lineup or sequence of entities.
- F. None of above.
Provenance (3 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71d6ba9c8190932f8d81240c3f56 |
completed | March 20, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3beb008190852fd6150813b252 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:32 p.m.