Triple
T19079775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shahabad region |
E466995
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Buxar |
—
|
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: Buxar | Statement: [Shahabad region, contains, Buxar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buxar Context triple: [Shahabad region, contains, Buxar]
-
A.
Buxar
chosen
Buxar is a historic town in the Indian state of Bihar, best known as the site of a pivotal 1764 battle that cemented British colonial dominance in northern India.
-
B.
Darbhanga
Darbhanga is a major city in the Indian state of Bihar, known as a cultural and educational center of the Mithila region.
-
C.
Karimganj
Karimganj is a town in the Indian state of Assam, known as a commercial and administrative center near the India–Bangladesh border.
-
D.
Jangipur
Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
-
E.
Bikapur
Bikapur is a town and administrative subdivision in the Ayodhya district of Uttar Pradesh, India, known for its proximity to the historic city of Ayodhya.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e82ec08190873186ff51e89d86 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 10, 2026, 12:04 p.m.