Triple
T20271557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azam Khan |
E499105
|
entity |
| Predicate | constituencyRepresented |
P192
|
FINISHED |
| Object | Rampur |
—
|
NE NERFINISHED |
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: [Azam Khan, constituencyRepresented, Rampur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rampur Context triple: [Azam Khan, constituencyRepresented, 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.
Rampur
Rampur is a town located in Nepal's Palpa District, known as one of the local settlements in the hilly western region of the country.
-
D.
Rampur Bushahr
Rampur Bushahr is a historic town in Himachal Pradesh, India, that once served as the capital of the princely state of Bushahr and remains an important cultural and trading center in the Sutlej Valley.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675de35188190840dc7d04c1d5fd9 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.