Triple
T2756892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jharkhand |
E61121
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Jamshedpur |
E167987
|
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: Jamshedpur | Statement: [Jharkhand, hasMajorCity, Jamshedpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamshedpur Context triple: [Jharkhand, hasMajorCity, Jamshedpur]
-
A.
Bhilai
Bhilai is an industrial city in central India best known for its large steel plant and planned urban infrastructure.
-
B.
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.
-
C.
Jehanabad
Jehanabad is a town and administrative district headquarters in the eastern Indian state of Bihar, known for its agricultural economy and proximity to the state capital, Patna.
-
D.
Gorakhpur
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
E.
Jamshedpur industrial region
chosen
Jamshedpur industrial region is a major steel and engineering hub in eastern India, centered around the city of Jamshedpur and dominated by large-scale industries such as Tata Steel.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8a292c8190ab3982434805241a |
completed | March 7, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08633e4108190a783b29a10efcc76 |
completed | March 10, 2026, 8:59 p.m. |
Created at: March 6, 2026, 9:56 p.m.