Triple
T13712408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babatpur |
E328805
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Azamgarh |
E477965
|
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: Azamgarh | Statement: [Babatpur, roadConnection, Azamgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azamgarh Context triple: [Babatpur, roadConnection, Azamgarh]
-
A.
Azamgarh
chosen
Azamgarh is a city in the Purvanchal region of eastern Uttar Pradesh, India, known as an important cultural and educational center.
-
B.
Amroha
Amroha is a town and municipal board in Uttar Pradesh, India, known for its historical significance and cultural heritage.
-
C.
Jaunpur
Jaunpur is a historic city in the Indian state of Uttar Pradesh, known for its medieval architecture and cultural heritage.
-
D.
Ghazipur
Ghazipur is a city in the Indian state of Uttar Pradesh, known for its historical significance and as a regional hub in eastern Uttar Pradesh.
-
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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd4395e8c0819098719c8cd344aa33 |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce6254e88190b6b4541fa22dc508 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 9:54 p.m.