Triple
T31645249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabhi |
E807567
|
entity |
| Predicate | popularComposition |
P37585
|
FINISHED |
| Object | Sāmi ninnē koriya (Tyagaraja) |
—
|
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: Sāmi ninnē koriya (Tyagaraja) | Statement: [Arabhi, popularComposition, Sāmi ninnē koriya (Tyagaraja)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularComposition Context triple: [Arabhi, popularComposition, Sāmi ninnē koriya (Tyagaraja)]
-
A.
popular
Indicates that an entity is widely liked, admired, or favored by many people compared to alternatives.
-
B.
featuredComposition
chosen
Indicates that one entity is highlighted or prominently presented as a notable composition in relation to another entity (such as a collection, event, or creator).
-
C.
popularFrom
Indicates that something gains or holds popularity starting from a specific time, source, or context.
-
D.
specialComposition
Indicates that one entity is composed of another in a distinctive or non-standard way, highlighting a particular or exceptional form of composition between them.
-
E.
popularDescription
Indicates that an entity has a commonly used or widely recognized descriptive text or label associated with it.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 30, 2026, 10:50 p.m.