Triple
T20271706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Connection (Buffalo Sabres line) |
E499108
|
entity |
| Predicate | playerWithNumber14 |
P60614
|
FINISHED |
| Object | Rene Robert |
—
|
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: Rene Robert | Statement: [French Connection (Buffalo Sabres line), playerWithNumber14, Rene Robert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playerWithNumber14 Context triple: [French Connection (Buffalo Sabres line), playerWithNumber14, Rene Robert]
-
A.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
jerseyNumberTeam
Indicates the association between a specific jersey number and the team for which that jersey number is used or assigned.
-
C.
quarterbackNumber
Indicates the jersey number assigned to a particular quarterback.
-
D.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
E.
playerNumber
chosen
Indicates the specific jersey or identification number assigned to a player within a team or game context.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675de35188190840dc7d04c1d5fd9 |
completed | April 20, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:42 p.m.