Triple
T17397648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorakhpur Junction railway station |
E422994
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Gorakhpur city |
—
|
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: Gorakhpur city | Statement: [Gorakhpur Junction railway station, serves, Gorakhpur city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorakhpur city Context triple: [Gorakhpur Junction railway station, serves, Gorakhpur city]
-
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.
Kashipur
Kashipur is a town in the Udham Singh Nagar district of Uttarakhand, India, known as an important industrial and commercial center in the region.
-
C.
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.
-
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.
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 (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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abe6f708190944aad636e1eb9a1 |
completed | April 19, 2026, 2:15 a.m. |
Created at: April 10, 2026, 5:45 a.m.