Triple
T21109534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandalwood (Kannada cinema) |
E520136
|
entity |
| Predicate | hasNotableCity |
P2813
|
FINISHED |
| Object | Mysuru |
—
|
NE NERFINISHED |
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: Mysuru | Statement: [Sandalwood (Kannada cinema), hasNotableCity, Mysuru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mysuru Context triple: [Sandalwood (Kannada cinema), hasNotableCity, Mysuru]
-
A.
Mysuru
chosen
Mysuru is a historic city in the southern Indian state of Karnataka, renowned for its royal heritage, palaces, and cultural festivals such as Dasara.
-
B.
Madikeri
Madikeri is a scenic hill town in Karnataka’s Coorg region, known for its cool climate, coffee plantations, and lush Western Ghats landscapes.
-
C.
Davangere
Davangere is a major city in central Karnataka, India, known for its textile industry, educational institutions, and distinctive local cuisine such as Davangere benne dosa.
-
D.
Sullia
Sullia is a town in the Dakshina Kannada district of Karnataka, India, known as a local commercial and educational center in the region.
-
E.
Vijayapura
Vijayapura is a historic city in the Indian state of Karnataka, renowned for its rich Deccan-era architecture and monuments such as the Gol Gumbaz.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7210110a48190a6359b6732f6293d |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.