Triple
T7016318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hooghly district |
E162707
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bandel |
E162703
|
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: Bandel | Statement: [Hooghly district, containsCity, Bandel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bandel Context triple: [Hooghly district, containsCity, Bandel]
-
A.
Bandel
chosen
Bandel is a historic town in West Bengal, India, known for its riverside location, colonial-era heritage, and the prominent Bandel Church.
-
B.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
C.
Benipatti
Benipatti is a town in the Madhubani district of the Indian state of Bihar, known for its rural setting and proximity to the region’s famed Mithila culture.
-
D.
Parbhani
Parbhani is a significant city in the Marathwada region of Maharashtra, India, known as an important commercial and educational center.
-
E.
Bairat
Bairat is a historic town in Rajasthan, India, known for its ancient Buddhist archaeological remains and connections to the Mauryan period.
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1d43e948190843f1cef3ce2004e |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775656fe48190a9690f5aaca3ba4c |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:34 p.m.