Triple
T21298666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhandara district |
E524995
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Tumsar
Tumsar is a town in the Bhandara district of Maharashtra, India, known for its regional commerce and proximity to agricultural and mining areas.
|
E1475860
|
NE FINISHED |
How this triple was built (4 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: Tumsar | Statement: [Bhandara district, hasTown, Tumsar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tumsar Context triple: [Bhandara district, hasTown, Tumsar]
-
A.
Arwal
Arwal is a small town and administrative center in the Indian state of Bihar, known for its agrarian surroundings and proximity to larger regional hubs.
-
B.
Champhai
Champhai is a town in the Indian state of Mizoram, known as a major commercial and cultural hub near the India–Myanmar border.
-
C.
Mangaldoi
Mangaldoi is a town in the Indian state of Assam that serves as an important administrative and commercial center for the surrounding region.
-
D.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
-
E.
Kokrajhar
Kokrajhar is a town in the Indian state of Assam that serves as the administrative and political center of the Bodoland Territorial Region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tumsar Triple: [Bhandara district, hasTown, Tumsar]
Generated description
Tumsar is a town in the Bhandara district of Maharashtra, India, known for its regional commerce and proximity to agricultural and mining areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tumsar Target entity description: Tumsar is a town in the Bhandara district of Maharashtra, India, known for its regional commerce and proximity to agricultural and mining areas.
-
A.
Arwal
Arwal is a small town and administrative center in the Indian state of Bihar, known for its agrarian surroundings and proximity to larger regional hubs.
-
B.
Champhai
Champhai is a town in the Indian state of Mizoram, known as a major commercial and cultural hub near the India–Myanmar border.
-
C.
Mangaldoi
Mangaldoi is a town in the Indian state of Assam that serves as an important administrative and commercial center for the surrounding region.
-
D.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
-
E.
Kokrajhar
Kokrajhar is a town in the Indian state of Assam that serves as the administrative and political center of the Bodoland Territorial Region.
- F. None of above. chosen
Provenance (5 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385a24d08190bfd410c7f10fa6f7 |
completed | April 21, 2026, 8:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a099814529c8190a94cfd3355862d0f |
completed | May 17, 2026, 10:27 a.m. |
| NEDg | Description generation | batch_6a0998b0c09081909f99cdd4064f55cc |
completed | May 17, 2026, 10:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09993444c88190a5f594315b81c34a |
completed | May 17, 2026, 10:32 a.m. |
Created at: April 16, 2026, 4:04 p.m.