Triple
T13591030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talacauvery |
E324691
|
entity |
| Predicate | administrativeDistrict |
P2709
|
FINISHED |
| Object | Kodagu |
E325183
|
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: Kodagu | Statement: [Talacauvery, administrativeDistrict, Kodagu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kodagu Context triple: [Talacauvery, administrativeDistrict, Kodagu]
-
A.
Kaniguram
Kaniguram is a historic town in South Waziristan, Pakistan, known as a traditional center of the Ormur (Burki) ethnic community.
-
B.
Kayadhu
Kayadhu is a figure in Hindu mythology known as the wife of the demon king Hiranyakashipu and the mother of the devotee Prahlada.
-
C.
Kolathunadu
Kolathunadu was a prominent medieval kingdom and historical region in northern Kerala, India, ruled by the Kolathiri dynasty and centered around present-day Kannur.
-
D.
Kodagu district
chosen
Kodagu district is a hilly, coffee-growing region in the Western Ghats of Karnataka, India, known for its scenic landscapes, rich biodiversity, and distinct Kodava culture.
-
E.
Kodaikanal
Kodaikanal is a popular hill station in southern India known for its cool climate, scenic lakes, and lush, forested landscapes.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f8ffc508190a7bc69745c43a644 |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:49 p.m.