Triple
T29615120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maro Charitra |
E754838
|
entity |
| Predicate | languagePairInStory |
P25926
|
FINISHED |
| Object | Telugu and Tamil |
—
|
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: Telugu and Tamil | Statement: [Maro Charitra, languagePairInStory, Telugu and Tamil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languagePairInStory Context triple: [Maro Charitra, languagePairInStory, Telugu and Tamil]
-
A.
languagePair
chosen
Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
-
B.
languageOfPrimaryNarrations
Indicates the language in which the main or primary narrations are expressed or conveyed.
-
C.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
D.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
E.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: April 28, 2026, 6:31 p.m.