Triple
T24834094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Wyatt |
E621419
|
entity |
| Predicate | supportingRoleTo |
P7748
|
FINISHED |
| Object | Leslie Knope’s political career |
—
|
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: Leslie Knope’s political career | Statement: [Ben Wyatt, supportingRoleTo, Leslie Knope’s political career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportingRoleTo Context triple: [Ben Wyatt, supportingRoleTo, Leslie Knope’s political career]
-
A.
supportingCharacter
chosen
Indicates that one entity plays a secondary or assisting role in the story or context relative to another primary entity.
-
B.
supportingActressRole
Indicates that an actress performs a supporting (non-leading) role in a particular production or work.
-
C.
supportingCharacterPortrayedBy
Indicates that a supporting (non-leading) character in a work is portrayed or acted by a specific performer.
-
D.
possibleRole
Indicates that an entity is capable of or eligible to serve in a particular role or function in a given context.
-
E.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69e2fac185d48190a0a6073ad1f6b792 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 18, 2026, 5:17 a.m.