Triple
T22646827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Central Railway |
E558985
|
entity |
| Predicate | headquarters |
P62
|
FINISHED |
| Object | Hajipur |
—
|
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: Hajipur | Statement: [East Central Railway, headquarters, Hajipur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hajipur Context triple: [East Central Railway, headquarters, Hajipur]
-
A.
Hajipur
chosen
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.
-
B.
Bhadohi
Bhadohi is a city in Uttar Pradesh, India, renowned as a major center for carpet weaving and often referred to as the "Carpet City" of the country.
-
C.
Indirapuram
Indirapuram is a prominent residential and commercial suburb in Ghaziabad, Uttar Pradesh, located on the eastern edge of Delhi and known for its high-rise apartments and proximity to the Delhi Metro.
-
D.
Harishpur
Harishpur is a historical port town in the Indian state of Odisha that served as an important maritime outlet during the Mughal period.
-
E.
Saharanpur
Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f170382ba48190b77692762db43313 |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:05 p.m.