Triple
T1598152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tikkana |
E34330
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | తిక్కన సోమయాజి |
E34330
|
NE 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: తిక్కన సోమయాజి | Statement: [Tikkana, nativeName, తిక్కన సోమయాజి]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: తిక్కన సోమయాజి Context triple: [Tikkana, nativeName, తిక్కన సోమయాజి]
-
A.
TIJ
TIJ is the IATA airport code for Tijuana International Airport in Tijuana, Mexico.
-
B.
Tilakkam
Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
-
C.
Tikkana
chosen
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
-
D.
Tilottama Sambhab
Tilottama Sambhab is a Bengali literary work by 19th-century poet and dramatist Michael Madhusudan Dutt, reflecting his pioneering role in modern Bengali literature.
-
E.
Venkata
Venkata is the given name of Indian physicist and Nobel laureate C. V. Raman, renowned for discovering the Raman effect in light scattering.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9092f5f148190b987bc943e89e29c |
completed | March 5, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad46a848ec819085c82be8eaea2044 |
completed | March 8, 2026, 9:51 a.m. |
Created at: March 4, 2026, 7:27 p.m.