Triple
T2964002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marwar |
E80117
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Thar Desert |
E5064
|
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: Thar Desert | Statement: [Marwar, locatedIn, Thar Desert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thar Desert Context triple: [Marwar, locatedIn, Thar Desert]
-
A.
Thar Desert
chosen
The Thar Desert is a vast arid region in northwestern India and eastern Pakistan, known for its sand dunes, extreme climate, and sparse vegetation.
-
B.
Nefud Desert
The Nefud Desert is a vast, crescent-shaped sand desert in northern Saudi Arabia known for its towering dunes and harsh, arid climate.
-
C.
Błędów Desert
Błędów Desert is a rare inland sand desert in southern Poland, known for its extensive dunes and unique, almost desert-like landscape.
-
D.
Aralkum Desert
The Aralkum Desert is a man-made desert that formed on the former seabed of the rapidly shrinking Aral Sea in Central Asia.
-
E.
Chagai Desert
The Chagai Desert is an arid region in western Balochistan, Pakistan, known for its harsh landscape and sparse population.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9958b1e48190a77f37bf63333c5b |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28de24f9881908396d263c4e21a04 |
completed | March 12, 2026, 9:56 a.m. |
Created at: March 8, 2026, 2:58 p.m.