Triple
T26533300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don (1978 film) |
E670876
|
entity |
| Predicate | featuresDualRole |
P188071
|
FINISHED |
| Object | Amitabh Bachchan |
—
|
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: Amitabh Bachchan | Statement: [Don (1978 film), featuresDualRole, Amitabh Bachchan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDualRole Context triple: [Don (1978 film), featuresDualRole, Amitabh Bachchan]
-
A.
dualUse
Indicates that something serves both civilian and military (or peaceful and non-peaceful) purposes simultaneously.
-
B.
dualPair
Indicates that two entities form a dual pair, standing in a mathematically defined dual relationship where each is the dual counterpart of the other.
-
C.
supportsDualSIM
Indicates that one entity provides or enables the use of two SIM cards simultaneously or interchangeably in another entity.
-
D.
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.
-
E.
dualLicensed
Indicates that an entity is simultaneously licensed under two distinct licenses or licensing regimes.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fba28684208190921694f23e350c3b |
completed | May 6, 2026, 8:20 p.m. |
Created at: April 27, 2026, 1:37 a.m.