Triple
T3774847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil literature |
E83282
|
entity |
| Predicate | notablePoeticForm |
P30317
|
FINISHED |
| Object | paripaadal |
E202402
|
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: paripaadal | Statement: [Tamil literature, notablePoeticForm, paripaadal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: paripaadal Context triple: [Tamil literature, notablePoeticForm, paripaadal]
-
A.
Parap
Parap is an inner-city suburb of Darwin in Australia's Northern Territory, known for its popular weekend markets and tropical, laid-back atmosphere.
-
B.
Palilula
Palilula is one of the urban municipalities of Belgrade, Serbia, encompassing both central city neighborhoods and outlying suburban and rural areas.
-
C.
Paripāṭal
chosen
Paripāṭal is a classical Tamil poetic anthology from the Sangam era, notable for its devotional and landscape-themed poems composed to specific musical tunes.
-
D.
Malaipadukadām
Malaipadukadām is a classical Tamil poem from the Sangam era renowned for its vivid portrayal of mountainous landscapes, tribal life, and romantic love.
-
E.
PAR
PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc594c50819099ab5ac1b82f61a6 |
completed | March 8, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e52ebd988190b6e3a7d8069b74be |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:36 p.m.