Triple
T17156190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dahod district |
E416348
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Rajasthan |
E9756
|
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: Rajasthan | Statement: [Dahod district, borderedBy, Rajasthan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rajasthan Context triple: [Dahod district, borderedBy, Rajasthan]
-
A.
Rajasthan
chosen
Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
-
B.
Gujarat
Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
-
C.
Jaipur State
Jaipur State was a prominent princely state in pre-independence India, ruled by Rajput kings from the Kachwaha dynasty with its capital at the historic city of Jaipur.
-
D.
Rajasthan (Malwa area)
Rajasthan (Malwa area) is a historic region in central India known for its distinctive Malwa painting tradition and rich Rajput-era cultural heritage.
-
E.
Chhattisgarh
Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40b402881908b8c01d7b957d0d2 |
completed | April 18, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fbff4b48190970073eb3b9d5d75 |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:37 a.m.