Triple
T10084242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rampur district |
E215178
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Rampur |
E231615
|
NE FINISHED |
How this triple was built (2 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: Rampur | Statement: [Rampur district, largestCity, Rampur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rampur Context triple: [Rampur district, largestCity, Rampur]
-
A.
Rampur
Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
-
B.
Rampur
chosen
Rampur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known historically for its princely state heritage and distinctive Rampuri culture.
-
C.
Saharanpur
Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
-
D.
Hamirpur
Hamirpur is a town and district headquarters in the Bundelkhand region of Uttar Pradesh, India, known for its location near the confluence of the Yamuna and Betwa rivers.
-
E.
Hajipur
Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd044c1ec8190b5b48cdb0584d00c |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e583ec2c819086429bd6d323d780 |
completed | April 5, 2026, 10:43 p.m. |
Created at: March 30, 2026, 9 p.m.