Triple
T33499176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pehla Nasha |
E857943
|
entity |
| Predicate | featuresCameoAppearance |
P49662
|
FINISHED |
| Object | Aamir Khan |
E85234
|
NE 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: Aamir Khan | Statement: [Pehla Nasha, featuresCameoAppearance, Aamir Khan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCameoAppearance Context triple: [Pehla Nasha, featuresCameoAppearance, Aamir Khan]
-
A.
featuresCameoBy
chosen
Indicates that a work includes a brief, often special-appearance role performed by the specified person or entity.
-
B.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
C.
mediaAppearanceWith
Indicates that two or more entities appeared together in the same media context, such as a show, interview, article, or broadcast.
-
D.
mediaAppearanceType
Indicates the specific kind or category of media appearance associated with an entity (e.g., interview, feature, cameo, or performance).
-
E.
appearanceInImages
Indicates that an entity is visually present or depicted within one or more images.
- F. None of above.
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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01b50490e481908eb1d675561fdde2 |
completed | May 11, 2026, 10:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37211362908190afcbbe30f5b5711c |
completed | June 20, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_6a01b44b106481908aa98a3f1eb2c119 |
completed | May 11, 2026, 10:49 a.m. |
Created at: May 1, 2026, 1:38 a.m.