Triple
T7976193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gondia district |
E185451
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Amgaon
Amgaon is a town in the Gondia district of Maharashtra, India, known as a local administrative and commercial center for surrounding rural areas.
|
E710049
|
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: Amgaon | Statement: [Gondia district, hasTown, Amgaon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amgaon Context triple: [Gondia district, hasTown, Amgaon]
-
A.
Chamkoria
Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
-
B.
Bhadgaon
Bhadgaon is another name for Bhaktapur, a historic Newar city in the Kathmandu Valley of Nepal renowned for its well-preserved medieval architecture, art, and culture.
-
C.
Khamgaon
Khamgaon is a city in the Buldhana district of Maharashtra, India, known as a regional commercial and educational center.
-
D.
Bhatapara
Bhatapara is a regional dialect of the Chhattisgarhi language spoken in and around the town of Bhatapara in the Indian state of Chhattisgarh.
-
E.
Arambagh
Arambagh is a town and administrative subdivision in the Hooghly district of West Bengal, India, known as a local commercial and transportation hub for the surrounding rural areas.
- 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: Amgaon Triple: [Gondia district, hasTown, Amgaon]
Generated description
Amgaon is a town in the Gondia district of Maharashtra, India, known as a local administrative and commercial center for surrounding rural areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amgaon Target entity description: Amgaon is a town in the Gondia district of Maharashtra, India, known as a local administrative and commercial center for surrounding rural areas.
-
A.
Chamkoria
Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
-
B.
Bhadgaon
Bhadgaon is another name for Bhaktapur, a historic Newar city in the Kathmandu Valley of Nepal renowned for its well-preserved medieval architecture, art, and culture.
-
C.
Khamgaon
Khamgaon is a city in the Buldhana district of Maharashtra, India, known as a regional commercial and educational center.
-
D.
Bhatapara
Bhatapara is a regional dialect of the Chhattisgarhi language spoken in and around the town of Bhatapara in the Indian state of Chhattisgarh.
-
E.
Arambagh
Arambagh is a town and administrative subdivision in the Hooghly district of West Bengal, India, known as a local commercial and transportation hub for the surrounding rural areas.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf56f688190902b95afe42635ec |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63b72c508190b0ad8acf975c1527 |
completed | April 1, 2026, 12:15 a.m. |
| NEDg | Description generation | batch_69cc68634dc88190bc9b9e0598929d4d |
completed | April 1, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc6946aa5481908d682957b818a3e9 |
completed | April 1, 2026, 12:39 a.m. |
Created at: March 30, 2026, 5:14 p.m.