Triple
T14684175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government House, Nagpur |
E344865
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Berar |
E305708
|
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: Berar | Statement: [Government House, Nagpur, associatedWith, Berar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berar Context triple: [Government House, Nagpur, associatedWith, Berar]
-
A.
Berar
chosen
Berar was a historical region in central India that became a significant Maratha-ruled province, later integrated into British India and now largely part of Maharashtra.
-
B.
Bergharen
Bergharen is a village in the Dutch province of Gelderland, known for its historic church and rural surroundings.
-
C.
Bereina
Bereina is a small town in Papua New Guinea’s Central Province, known primarily as a rural administrative and service center for surrounding villages.
-
D.
Norén
Norén is a Swedish surname, notably borne by actress Noomi Rapace before she adopted her stage name.
-
E.
Harestua
Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56bdb8081909ff86440ba20fb1f |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde18592088190892ae1cc371165be |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:28 a.m.