Triple
T15648234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banaskantha district |
E376236
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Radhanpur
Radhanpur is a town in the Banaskantha district of Gujarat, India, known historically as a former princely state and regional trading center.
|
E1170559
|
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: Radhanpur | Statement: [Banaskantha district, hasTown, Radhanpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radhanpur Context triple: [Banaskantha district, hasTown, Radhanpur]
-
A.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
B.
Gadarpur
Gadarpur is a town in the Udham Singh Nagar district of Uttarakhand, India, known primarily as an agricultural and trading center in the Terai region.
-
C.
Tekanpur
Tekanpur is a town in Madhya Pradesh, India, best known for hosting the Border Security Force’s main training academy.
-
D.
Rajesultanpur
Rajesultanpur is a town in the Indian state of Uttar Pradesh known as one of the key urban centers of Ambedkar Nagar district.
-
E.
Mahipalpur
Mahipalpur is an urban village and commercial area in Delhi, India, located near Indira Gandhi International Airport and known for its hotels, transport hubs, and proximity to major highways.
- 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: Radhanpur Triple: [Banaskantha district, hasTown, Radhanpur]
Generated description
Radhanpur is a town in the Banaskantha district of Gujarat, India, known historically as a former princely state and regional trading center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Radhanpur Target entity description: Radhanpur is a town in the Banaskantha district of Gujarat, India, known historically as a former princely state and regional trading center.
-
A.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
B.
Gadarpur
Gadarpur is a town in the Udham Singh Nagar district of Uttarakhand, India, known primarily as an agricultural and trading center in the Terai region.
-
C.
Tekanpur
Tekanpur is a town in Madhya Pradesh, India, best known for hosting the Border Security Force’s main training academy.
-
D.
Rajesultanpur
Rajesultanpur is a town in the Indian state of Uttar Pradesh known as one of the key urban centers of Ambedkar Nagar district.
-
E.
Mahipalpur
Mahipalpur is an urban village and commercial area in Delhi, India, located near Indira Gandhi International Airport and known for its hotels, transport hubs, and proximity to major highways.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed7212c8190be6ff76afa25f7ca |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ed4d9f88190b7e24bf84c5a916f |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6fe77b408190960b544d4a22587d |
completed | May 9, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff703fe0088190ab5578d3d398ca09 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 10, 2026, 4:15 a.m.