Triple
T7045039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoysalas |
E163610
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Halebidu |
E641465
|
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: Halebidu | Statement: [Hoysalas, capital, Halebidu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halebidu Context triple: [Hoysalas, capital, Halebidu]
-
A.
Belur
Belur is a locality in the Howrah district of West Bengal, India, known for its proximity to the Hooghly River and the famous Belur Math.
-
B.
Belur
chosen
Belur is a historic town in Karnataka, India, renowned for its exquisite Hoysala-era temple architecture, especially the Chennakeshava Temple.
-
C.
Hampi
Hampi is an ancient ruined city in Karnataka, India, famed for its monumental Hindu temples and as the former capital of the Vijayanagara Empire.
-
D.
Badami
Badami is a historic town in Karnataka, India, renowned for its rock-cut cave temples and ancient Chalukyan architecture.
-
E.
Devanahalli
Devanahalli is a town near Bengaluru in the Indian state of Karnataka, notable for its rapid development and proximity to Kempegowda International Airport.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e238c7a4819095f5ff7283d48da8 |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a313f0c88190834daf87723a77a1 |
completed | March 28, 2026, 9:44 a.m. |
Created at: March 27, 2026, 2:37 p.m.