Triple
T29332503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thillu Mullu |
E743816
|
entity |
| Predicate | portraysDoubleRole |
P192492
|
FINISHED |
| Object | Rajinikanth |
—
|
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: Rajinikanth | Statement: [Thillu Mullu, portraysDoubleRole, Rajinikanth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysDoubleRole Context triple: [Thillu Mullu, portraysDoubleRole, Rajinikanth]
-
A.
portraysRoleTrait
Indicates that one entity depicts or represents a particular role or character trait of another entity.
-
B.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
C.
bilateralRole
Indicates a relationship where each of two entities holds a defined role with respect to the other in a mutual or two-sided interaction.
-
D.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
E.
depictsPersonRole
Indicates that an image or representation shows a person in a specific role, function, or capacity.
- F. None of above. chosen
Provenance (4 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: April 28, 2026, 1:30 p.m.