Triple
T1802823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil cinema |
E39755
|
entity |
| Predicate | hasGlobalRecognitionFor |
P753
|
FINISHED |
| Object | A. R. Rahman’s film scores |
—
|
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: A. R. Rahman’s film scores | Statement: [Tamil cinema, hasGlobalRecognitionFor, A. R. Rahman’s film scores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlobalRecognitionFor Context triple: [Tamil cinema, hasGlobalRecognitionFor, A. R. Rahman’s film scores]
-
A.
recognizedFor
chosen
Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work associated with another entity.
-
B.
haveInternationalRecognition
Indicates that an entity is formally acknowledged or accepted by the international community or by official bodies across multiple countries.
-
C.
recognizedIn
Indicates that an entity is formally acknowledged, honored, or given recognition within a particular context, setting, or domain.
-
D.
canRecognize
Indicates that one entity has the ability to identify or distinguish another entity based on its features or characteristics.
-
E.
hasGlobalReach
Indicates that an entity’s influence, operations, or impact extends across multiple countries or worldwide.
- 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d514c081908197ac1f7c7d7a88 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.