Triple
T5126379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nāṭyaśāstra |
E115593
|
entity |
| Predicate | listsAbhinayaType |
P62672
|
FINISHED |
| Object | āṅgika abhinaya |
—
|
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: āṅgika abhinaya | Statement: [Nāṭyaśāstra, listsAbhinayaType, āṅgika abhinaya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: listsAbhinayaType Context triple: [Nāṭyaśāstra, listsAbhinayaType, āṅgika abhinaya]
-
A.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
B.
theatricalMovement
Indicates a relationship where an entity is associated with, participates in, or exemplifies a particular theatrical movement or style within the performing arts.
-
C.
balletType
Indicates that one entity is classified as a specific type or category of ballet in relation to another entity.
-
D.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
E.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7d5a23908190a24e79d1b29d6fcf |
completed | March 20, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69bd77aa68b88190a50dd736a72d2901 |
completed | March 20, 2026, 4:36 p.m. |
| PDg | Predicate description generation | batch_69bd7d5906d88190b805977e5a05767a |
completed | March 20, 2026, 5:01 p.m. |
Created at: March 20, 2026, 1:42 p.m.