Triple
T10223308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mancherial district |
E242635
|
entity |
| Predicate | hasUrbanCenter |
P2106
|
FINISHED |
| Object |
Bellampalli
Bellampalli is a coal-mining town in the Indian state of Telangana, known for its numerous collieries and role in the Singareni coalfields.
|
E850509
|
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: Bellampalli | Statement: [Mancherial district, hasUrbanCenter, Bellampalli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bellampalli Context triple: [Mancherial district, hasUrbanCenter, Bellampalli]
-
A.
Tadipatri
Tadipatri is a town in the Anantapur district of Andhra Pradesh, India, known for its granite industries and historic temples.
-
B.
Banaganapalle
Banaganapalle is a town and legislative assembly constituency in the Nandyal district of Andhra Pradesh, India, known historically for its mangoes and regional political significance.
-
C.
Nallapadu
Nallapadu is a locality and railway junction near Guntur in Andhra Pradesh, India, serving as a regional rail hub.
-
D.
Narayanavanam
Narayanavanam is a small town in the Tirupati district of Andhra Pradesh, India, known for its historic temples and religious significance.
-
E.
Peddapuram
Peddapuram is a town in the Indian state of Andhra Pradesh known for its historical significance and regional commerce.
- 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: Bellampalli Triple: [Mancherial district, hasUrbanCenter, Bellampalli]
Generated description
Bellampalli is a coal-mining town in the Indian state of Telangana, known for its numerous collieries and role in the Singareni coalfields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bellampalli Target entity description: Bellampalli is a coal-mining town in the Indian state of Telangana, known for its numerous collieries and role in the Singareni coalfields.
-
A.
Tadipatri
Tadipatri is a town in the Anantapur district of Andhra Pradesh, India, known for its granite industries and historic temples.
-
B.
Banaganapalle
Banaganapalle is a town and legislative assembly constituency in the Nandyal district of Andhra Pradesh, India, known historically for its mangoes and regional political significance.
-
C.
Nallapadu
Nallapadu is a locality and railway junction near Guntur in Andhra Pradesh, India, serving as a regional rail hub.
-
D.
Narayanavanam
Narayanavanam is a small town in the Tirupati district of Andhra Pradesh, India, known for its historic temples and religious significance.
-
E.
Peddapuram
Peddapuram is a town in the Indian state of Andhra Pradesh known for its historical significance and regional commerce.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa8305e481908ee1fc1d9eda6fa0 |
completed | April 6, 2026, 12:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a8457e9c819085f222bb002be892 |
completed | April 8, 2026, 7:11 p.m. |
| NEDg | Description generation | batch_69d6d00220ec81909d189e64eda2a28f |
completed | April 8, 2026, 10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6df44ad5481909100b596d2bf3b07 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 6, 2026, 11:10 a.m.