Triple
T10063477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malabar District |
E213042
|
entity |
| Predicate | containsRegion |
P285
|
FINISHED |
| Object | Wayanad |
E208519
|
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: Wayanad | Statement: [Malabar District, containsRegion, Wayanad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wayanad Context triple: [Malabar District, containsRegion, Wayanad]
-
A.
Wayanad
chosen
Wayanad is a scenic hill district in Kerala, India, known for its lush forests, wildlife sanctuaries, waterfalls, and spice plantations.
-
B.
Malabar District
Malabar District was a former administrative region in southwestern India under British rule, later incorporated into the state of Kerala.
-
C.
North Canara
North Canara is a coastal district in the Indian state of Karnataka, known for its Arabian Sea shoreline, Western Ghats forests, and diverse cultural and linguistic heritage.
-
D.
Kasargod district
Kasargod district is a northern Kerala district in India known for its linguistic diversity, coastal landscapes, and cultural blend of Kerala and neighboring Karnataka.
-
E.
Coorg
Coorg, also known as Kodagu, is a scenic hill district in Karnataka, India, famed for its coffee plantations, lush forests, and mist-covered 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcfd4e4ac8190a37061b4082caa48 |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b630ca008190a337660ad8c9d57e |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 8:58 p.m.