Triple
T11444323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amarkantak |
E271224
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Amarkantak plateau |
E55943
|
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: Amarkantak plateau | Statement: [Amarkantak, partOf, Amarkantak plateau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amarkantak plateau Context triple: [Amarkantak, partOf, Amarkantak plateau]
-
A.
Amarkantak Plateau
chosen
The Amarkantak Plateau is a highland region in central India known as a major watershed and pilgrimage site where several important rivers originate.
-
B.
Balaghat plateau
The Balaghat Plateau is a highland region in Maharashtra, India, characterized by its undulating terrain and agricultural landscapes.
-
C.
Betul Plateau
Betul Plateau is a highland region in central India that forms part of the Satpura Range, characterized by its elevated terrain and forested landscapes.
-
D.
Mount Abu plateau
Mount Abu plateau is a highland region in western India known for its cool climate, scenic landscapes, and the hill station of Mount Abu.
-
E.
Bundelkhand plateau
The Bundelkhand plateau is a rugged, semi-arid region of central India known for its rocky terrain, historical forts, and recurrent droughts spanning parts of Uttar Pradesh and Madhya Pradesh.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8088a66f48190b2b4a56cd62097cf |
completed | April 9, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e8f8049881909c1a52101e4620b3 |
completed | April 20, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:35 p.m.