Triple
T10149372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dungarpur State |
E232589
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Idar State |
E772541
|
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: Idar State | Statement: [Dungarpur State, borderedBy, Idar State]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Idar State Context triple: [Dungarpur State, borderedBy, Idar State]
-
A.
Idar State
chosen
Idar State was a princely state in western India during the British Raj, located in present-day Gujarat.
-
B.
Svarstad
Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
-
C.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
D.
Seljord
Seljord is a small Norwegian town known for its scenic lake, traditional cultural events, and the local legend of the Seljord Lake serpent.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec03e80c81909c813dae91c56272 |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e6369c848190984394eedf2f07eb |
completed | April 5, 2026, 10:46 p.m. |
Created at: March 30, 2026, 9:08 p.m.