Triple
T6304977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bareilly division |
E141351
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Shahjahanpur |
E280629
|
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: Shahjahanpur | Statement: [Bareilly division, hasCity, Shahjahanpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shahjahanpur Context triple: [Bareilly division, hasCity, Shahjahanpur]
-
A.
Shahjahanpur
chosen
Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
-
B.
Bulandshahr
Bulandshahr is a city in the Indian state of Uttar Pradesh known for its historical significance and proximity to Delhi within the broader metropolitan region.
-
C.
Jaunpur
Jaunpur is a historic city in the Indian state of Uttar Pradesh, known for its medieval architecture and cultural heritage.
-
D.
Moradabad
Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
-
E.
Farrukhabad
Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645f26a881909d5746151c0843cc |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7005e8c2c81909729f7ab3ae0287d |
completed | March 27, 2026, 10:10 p.m. |
Created at: March 22, 2026, 4:28 p.m.