Triple
T3065698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lion |
E62098
|
entity |
| Predicate | featuresActorAsRole |
P42172
|
FINISHED |
| Object | Dev Patel as adult Saroo Brierley |
—
|
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: Dev Patel as adult Saroo Brierley | Statement: [Lion, featuresActorAsRole, Dev Patel as adult Saroo Brierley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorAsRole Context triple: [Lion, featuresActorAsRole, Dev Patel as adult Saroo Brierley]
-
A.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
B.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
C.
playsInRole
chosen
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
D.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
E.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fc01dc81908fbdf7c1ef73afe4 |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.