Triple
T19937362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH 19 |
E479206
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Dhanbad |
—
|
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: Dhanbad | Statement: [NH 19, connectsCity, Dhanbad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dhanbad Context triple: [NH 19, connectsCity, Dhanbad]
-
A.
Dhanbad
chosen
Dhanbad is a major industrial city in eastern India, widely known as the "Coal Capital of India" for its extensive coal mining operations.
-
B.
Giridih
Giridih is a city in eastern India known for its coal and mica mining, situated in the Giridih district of the state of Jharkhand.
-
C.
Jharsuguda
Jharsuguda is a town and district in western Odisha, India, known as an industrial and mining hub where the Koshali language is widely spoken.
-
D.
Ranchi
Ranchi is the capital city of the Indian state of Jharkhand, known for its hilly terrain, waterfalls, and role as a regional political and commercial center.
-
E.
Jamshedpur
Jamshedpur is a major industrial city in eastern India, best known as the home of Tata Steel and one of the country’s earliest planned company towns.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a17fb2c8190b3aaae88e741648a |
completed | April 20, 2026, 4:53 p.m. |
Created at: April 10, 2026, 1:53 p.m.