Triple
T15566077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta Muldoon |
E371116
|
entity |
| Predicate | teamSportRole |
P13665
|
FINISHED |
| Object | professional player |
—
|
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: professional player | Statement: [Roberta Muldoon, teamSportRole, professional player]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamSportRole Context triple: [Roberta Muldoon, teamSportRole, professional player]
-
A.
lineupRole
Indicates the specific role or position an entity holds within a lineup or ordered group.
-
B.
associatedPlayerRole
Indicates a relationship where a specific role or function is linked to, or held by, a particular player.
-
C.
roleAtSportsTeam
chosen
Indicates the specific position or function an individual holds within a sports team.
-
D.
roleInRugby
Indicates the specific position or function an entity holds within the context of playing or participating in rugby.
-
E.
hasSportsRole
Indicates that an entity holds or is assigned a specific role or position within a sports context or organization.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddd753c8190b51eaef433258081 |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.