Triple
T11673993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kushinagar |
E277445
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Gorakhpur |
E94443
|
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: Gorakhpur | Statement: [Kushinagar, near, Gorakhpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorakhpur Context triple: [Kushinagar, near, Gorakhpur]
-
A.
Gorakhpur
chosen
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
B.
Kishanganj
Kishanganj is a town and district headquarters in the northeastern part of the Indian state of Bihar, known for its significant Muslim population and proximity to the borders of West Bengal and Nepal.
-
C.
Bhagalpur
Bhagalpur is a historic city in the eastern Indian state of Bihar, known for its silk industry and location along the Ganges River.
-
D.
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.
-
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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a443b6848190a1eb6825fbc49d08 |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0192f790c8190a99d512b6f5c15aa |
completed | April 28, 2026, 2:19 a.m. |
Created at: April 8, 2026, 9:40 p.m.