Triple
T12789079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berar |
E305708
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Washim |
E491307
|
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: Washim | Statement: [Berar, majorCity, Washim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Washim Context triple: [Berar, majorCity, Washim]
-
A.
Washim
chosen
Washim is a city in the Vidarbha region of Maharashtra, India, known as an important local administrative and commercial center.
-
B.
Shiga
Shiga is a landlocked prefecture in central Japan known for encompassing Lake Biwa, the country’s largest freshwater lake, and for its historical sites and natural scenery.
-
C.
Washim district
Washim district is an administrative district in the Vidarbha region of Maharashtra, India, known for its predominantly agrarian economy and historical temples.
-
D.
Nakagawa
Nakagawa is a river in Japan, likely a tributary or neighboring waterway associated with the Edogawa River system.
-
E.
Tagawa
Tagawa is a small inland city in Japan known historically as a coal-mining center within Fukuoka Prefecture on Kyushu Island.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6a61f48190972e241e70bc392c |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68508e4488190bb57a1ade93987ab |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:30 p.m.