Triple
T15969135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akananuru |
E387273
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Ettuthokai |
E202399
|
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: Ettuthokai | Statement: [Akananuru, partOf, Ettuthokai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ettuthokai Context triple: [Akananuru, partOf, Ettuthokai]
-
A.
Ettuthokai
chosen
Ettuthokai is a classical Tamil anthology comprising eight collections of early Sangam poems that are central to ancient Tamil literature.
-
B.
Kalithokai
Kalithokai is an ancient Tamil poetic anthology, renowned as one of the classical Sangam literature collections.
-
C.
Urapakkam
Urapakkam is a rapidly developing suburban residential area on the outskirts of Chennai in Tamil Nadu, India.
-
D.
Kiasutha
Kiasutha is an alternative name for Guyasuta, a prominent 18th-century Seneca leader and diplomat involved in key events of the French and Indian War and early American history.
-
E.
Khoiniki
Khoiniki is a town in southeastern Belarus known for its proximity to the Chernobyl-affected areas and its role in regional administration and services.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe88fa308190942d37cf67458396 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:54 a.m.