Triple
T1477231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chhattisgarh |
E30868
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Korba
Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
|
E211365
|
NE FINISHED |
How this triple was built (4 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: Korba | Statement: [Chhattisgarh, hasMajorCity, Korba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korba Context triple: [Chhattisgarh, hasMajorCity, Korba]
-
A.
Narsinghpur
Narsinghpur is a city and administrative center in central India known for its agricultural economy, particularly sugarcane and pulses, within the state of Madhya Pradesh.
-
B.
Contai
Contai is a coastal town in eastern India known as a regional commercial and transport hub in the Purba Medinipur district of West Bengal.
-
C.
Bilaspur
Bilaspur is a major city in the Indian state of Chhattisgarh, known as an important administrative, commercial, and judicial center.
-
D.
Bhilai
Bhilai is an industrial city in central India best known for its large steel plant and planned urban infrastructure.
-
E.
Sambalpur
Sambalpur is a historic city and former princely region in western Odisha, India, known for its cultural heritage, textile traditions, and role in 19th-century colonial-era political events.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Korba Triple: [Chhattisgarh, hasMajorCity, Korba]
Generated description
Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Korba Target entity description: Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
-
A.
Narsinghpur
Narsinghpur is a city and administrative center in central India known for its agricultural economy, particularly sugarcane and pulses, within the state of Madhya Pradesh.
-
B.
Contai
Contai is a coastal town in eastern India known as a regional commercial and transport hub in the Purba Medinipur district of West Bengal.
-
C.
Bilaspur
Bilaspur is a major city in the Indian state of Chhattisgarh, known as an important administrative, commercial, and judicial center.
-
D.
Bhilai
Bhilai is an industrial city in central India best known for its large steel plant and planned urban infrastructure.
-
E.
Sambalpur
Sambalpur is a historic city and former princely region in western Odisha, India, known for its cultural heritage, textile traditions, and role in 19th-century colonial-era political events.
- F. None of above. chosen
Provenance (5 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c603f9e88190b340734709534860 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeabbc9588190880996e549b8bd7a |
completed | March 8, 2026, 9:31 p.m. |
| NEDg | Description generation | batch_69adeb6e8fe08190a4732d42aa15ee8e |
completed | March 8, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adebea03a08190bd055e3e6460b5f4 |
completed | March 8, 2026, 9:36 p.m. |
Created at: March 1, 2026, 8:11 p.m.