Triple
T23679289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venkata Narasimha Raju Varma |
E584972
|
entity |
| Predicate | hasTraditionalIndianName |
P17611
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Venkata Narasimha Raju Varma, hasTraditionalIndianName, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalIndianName Context triple: [Venkata Narasimha Raju Varma, hasTraditionalIndianName, true]
-
A.
hasTraditionalName
chosen
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
B.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
-
C.
hasJavaneseName
Indicates that an entity possesses a name expressed in the Javanese language.
-
D.
pairedTraditionalName
Indicates that two entities are associated as a traditional name pair, typically used together or in customary combination within a cultural or naming convention.
-
E.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f5a7b48190b93d27416003e173 |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.