Triple
T19815241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH 65 |
E476042
|
entity |
| Predicate | passesThroughCity |
P416
|
FINISHED |
| Object |
Suryapet
Suryapet is a major town and commercial hub in the Indian state of Telangana, known for its strategic location and connectivity between Hyderabad and Vijayawada.
|
E1398534
|
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: Suryapet | Statement: [NH 65, passesThroughCity, Suryapet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suryapet Context triple: [NH 65, passesThroughCity, Suryapet]
-
A.
Jangaon
Jangaon is a town and municipal center in the Indian state of Telangana, known for its location along key road and rail routes between Hyderabad and Warangal.
-
B.
Nandipet
Nandipet is a village located in the Nizamabad district of the Indian state of Telangana.
-
C.
Nalgonda
Nalgonda is a town and district headquarters in the Indian state of Telangana, known for its proximity to major irrigation projects and its historical significance in the region.
-
D.
Nandyal
Nandyal is a city in the Indian state of Andhra Pradesh, known as a commercial and administrative center in the Rayalaseema region.
-
E.
Tiptur
Tiptur is a town in the Indian state of Karnataka known for its coconut plantations and trade.
- 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: Suryapet Triple: [NH 65, passesThroughCity, Suryapet]
Generated description
Suryapet is a major town and commercial hub in the Indian state of Telangana, known for its strategic location and connectivity between Hyderabad and Vijayawada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suryapet Target entity description: Suryapet is a major town and commercial hub in the Indian state of Telangana, known for its strategic location and connectivity between Hyderabad and Vijayawada.
-
A.
Jangaon
Jangaon is a town and municipal center in the Indian state of Telangana, known for its location along key road and rail routes between Hyderabad and Warangal.
-
B.
Nandipet
Nandipet is a village located in the Nizamabad district of the Indian state of Telangana.
-
C.
Nalgonda
Nalgonda is a town and district headquarters in the Indian state of Telangana, known for its proximity to major irrigation projects and its historical significance in the region.
-
D.
Nandyal
Nandyal is a city in the Indian state of Andhra Pradesh, known as a commercial and administrative center in the Rayalaseema region.
-
E.
Tiptur
Tiptur is a town in the Indian state of Karnataka known for its coconut plantations and trade.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f861248190a633dd8d227d9697 |
completed | April 20, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07d42ffe7c8190b04c2ad6ea82438a |
completed | May 16, 2026, 2:19 a.m. |
| NEDg | Description generation | batch_6a07d4e943b081909f98c72683d62e62 |
completed | May 16, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d5bc8e748190a4f97e6b23e56edd |
completed | May 16, 2026, 2:26 a.m. |
Created at: April 10, 2026, 1:50 p.m.