Triple
T13321740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mysore Airport |
E317330
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Mysuru city centre |
E80753
|
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: Mysuru city centre | Statement: [Mysore Airport, locatedNear, Mysuru city centre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mysuru city centre Context triple: [Mysore Airport, locatedNear, Mysuru city centre]
-
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.
Melkote
Melkote is a historic temple town in Karnataka, India, renowned as a major Vaishnavite pilgrimage center and seat of the Cheluvanarayana Swamy and Yoga Narasimha temples.
-
C.
Marathahalli
Marathahalli is a major residential and commercial suburb in eastern Bangalore, known for its connectivity, IT parks, and shopping areas.
-
D.
Madikeri
Madikeri is a scenic hill town in Karnataka’s Coorg region, known for its cool climate, coffee plantations, and lush Western Ghats landscapes.
-
E.
Sullia
Sullia is a town in the Dakshina Kannada district of Karnataka, India, known as a local commercial and educational center in the region.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992ab83c8190982d9f54dff6919f |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7266cfb3c8190ac9ccb7696d02922 |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:30 p.m.