Triple
T18570709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aravinda de Silva |
E453865
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Aravinda |
—
|
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: Aravinda | Statement: [Aravinda de Silva, givenName, Aravinda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aravinda Context triple: [Aravinda de Silva, givenName, Aravinda]
-
A.
Aravind
chosen
Aravind is a masculine given name commonly used in India, often associated with meanings related to wisdom or the lotus flower.
-
B.
Arun
Arun is a local government district and borough in West Sussex, England, named after the River Arun and encompassing coastal towns such as Bognor Regis and Littlehampton.
-
C.
Arun
Arun is a masculine given name commonly used in South Asian cultures, often associated with the sun or dawn.
-
D.
Raghavendra
Raghavendra is a 2003 Telugu-language romantic drama film starring Prabhas in one of his early leading roles.
-
E.
Sukumar
Sukumar is a prominent Indian film director and screenwriter known for his psychologically layered storytelling and stylish Telugu-language films in the Tollywood industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b01331c8190bec3aba40358a843 |
completed | April 19, 2026, 8:28 p.m. |
Created at: April 10, 2026, 11:43 a.m.