Triple
T7364892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raniganj coalfield |
E169844
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Barakar
Barakar is a town in the Asansol region of West Bengal, India, known for its proximity to major coal mining operations and its location near the Barakar River.
|
E660094
|
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: Barakar | Statement: [Raniganj coalfield, containsTown, Barakar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barakar Context triple: [Raniganj coalfield, containsTown, Barakar]
-
A.
Ghoghardiha
Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
-
B.
Bagdogra
Bagdogra is a town in the Darjeeling district of West Bengal, India, known as a key gateway to the eastern Himalayas and nearby hill stations.
-
C.
Gobardanga
Gobardanga is a town in the Indian state of West Bengal known for its suburban character and connectivity to Kolkata via the Sealdah–Bangaon railway line.
-
D.
Shonkhonil Karagar
Shonkhonil Karagar is a popular Bengali novel by Humayun Ahmed, known for its poignant portrayal of family life and emotional depth.
-
E.
Cassimbazar
Cassimbazar was a prominent trading town in Bengal that served as an important commercial center for European powers, including the Dutch, during the early modern period.
- 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: Barakar Triple: [Raniganj coalfield, containsTown, Barakar]
Generated description
Barakar is a town in the Asansol region of West Bengal, India, known for its proximity to major coal mining operations and its location near the Barakar River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barakar Target entity description: Barakar is a town in the Asansol region of West Bengal, India, known for its proximity to major coal mining operations and its location near the Barakar River.
-
A.
Ghoghardiha
Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
-
B.
Bagdogra
Bagdogra is a town in the Darjeeling district of West Bengal, India, known as a key gateway to the eastern Himalayas and nearby hill stations.
-
C.
Gobardanga
Gobardanga is a town in the Indian state of West Bengal known for its suburban character and connectivity to Kolkata via the Sealdah–Bangaon railway line.
-
D.
Shonkhonil Karagar
Shonkhonil Karagar is a popular Bengali novel by Humayun Ahmed, known for its poignant portrayal of family life and emotional depth.
-
E.
Cassimbazar
Cassimbazar was a prominent trading town in Bengal that served as an important commercial center for European powers, including the Dutch, during the early modern period.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f161d76081909da6d698fb3d8bb1 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802b90cc081908b15e61921d15b92 |
completed | March 28, 2026, 4:32 p.m. |
| NEDg | Description generation | batch_69c804b776d081908e99c5dcfdcc47e2 |
completed | March 28, 2026, 4:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c80520f2088190888f39e8e6a462dc |
completed | March 28, 2026, 4:43 p.m. |
Created at: March 27, 2026, 3:06 p.m.