Triple
T7308353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rampur, Uttar Pradesh |
E168031
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object |
Rudrapur
Rudrapur is a town in the Indian state of Uttar Pradesh, known as a local commercial and agricultural center in the region.
|
E655947
|
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: Rudrapur | Statement: [Rampur, Uttar Pradesh, hasNearbyCity, Rudrapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rudrapur Context triple: [Rampur, Uttar Pradesh, hasNearbyCity, Rudrapur]
-
A.
Mukteshwar
Mukteshwar is a scenic hill town in Uttarakhand, India, known for its panoramic Himalayan views, fruit orchards, and tranquil forests.
-
B.
Nalhati
Nalhati is a town in the Birbhum district of West Bengal, India, known for its religious significance and regional marketplace.
-
C.
Uttarkashi
Uttarkashi is a town in the Indian state of Uttarakhand, known as a gateway to several Himalayan pilgrim sites and trekking routes along the upper Ganges.
-
D.
Bageshwar
Bageshwar is a town and district headquarters in the Kumaon region of Uttarakhand, India, known for its religious significance and scenic Himalayan surroundings.
-
E.
Kasauli
Kasauli is a small, picturesque hill station in the Indian state of Himachal Pradesh, known for its colonial-era architecture, pine forests, and tranquil atmosphere.
- 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: Rudrapur Triple: [Rampur, Uttar Pradesh, hasNearbyCity, Rudrapur]
Generated description
Rudrapur is a town in the Indian state of Uttar Pradesh, known as a local commercial and agricultural center in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rudrapur Target entity description: Rudrapur is a town in the Indian state of Uttar Pradesh, known as a local commercial and agricultural center in the region.
-
A.
Mukteshwar
Mukteshwar is a scenic hill town in Uttarakhand, India, known for its panoramic Himalayan views, fruit orchards, and tranquil forests.
-
B.
Nalhati
Nalhati is a town in the Birbhum district of West Bengal, India, known for its religious significance and regional marketplace.
-
C.
Uttarkashi
Uttarkashi is a town in the Indian state of Uttarakhand, known as a gateway to several Himalayan pilgrim sites and trekking routes along the upper Ganges.
-
D.
Bageshwar
Bageshwar is a town and district headquarters in the Kumaon region of Uttarakhand, India, known for its religious significance and scenic Himalayan surroundings.
-
E.
Kasauli
Kasauli is a small, picturesque hill station in the Indian state of Himachal Pradesh, known for its colonial-era architecture, pine forests, and tranquil atmosphere.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebda7b748190a230a22ecea79342 |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e56443b08190aee2c26633cdcbed |
completed | March 28, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_69c7e97659a08190a548beda4d7d6d9f |
completed | March 28, 2026, 2:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ea1847008190aae44d6eb9f572d4 |
completed | March 28, 2026, 2:47 p.m. |
Created at: March 27, 2026, 3:01 p.m.