Triple
T1418172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Bengal |
E31965
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Baharampur
Baharampur is a major town and administrative center in the Murshidabad district of the Indian state of West Bengal, known for its historical significance and regional commerce.
|
E184769
|
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: Baharampur | Statement: [West Bengal, containsTown, Baharampur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baharampur Context triple: [West Bengal, containsTown, Baharampur]
-
A.
Burhanpur
Burhanpur is a historic city in central India known for its Mughal-era architecture and strategic location on the banks of the Tapti River.
-
B.
Kalipur
Kalipur is a coastal village and notable settlement on North Andaman Island in India’s Andaman and Nicobar archipelago, known for its beaches and natural surroundings.
-
C.
Jahangir Nagar
Jahangir Nagar is the former Mughal-era name of present-day Dhaka, given in honor of the emperor Jahangir.
-
D.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
E.
Krishnanagar
Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
- 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: Baharampur Triple: [West Bengal, containsTown, Baharampur]
Generated description
Baharampur is a major town and administrative center in the Murshidabad district of the Indian state of West Bengal, known for its historical significance and regional commerce.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baharampur Target entity description: Baharampur is a major town and administrative center in the Murshidabad district of the Indian state of West Bengal, known for its historical significance and regional commerce.
-
A.
Burhanpur
Burhanpur is a historic city in central India known for its Mughal-era architecture and strategic location on the banks of the Tapti River.
-
B.
Kalipur
Kalipur is a coastal village and notable settlement on North Andaman Island in India’s Andaman and Nicobar archipelago, known for its beaches and natural surroundings.
-
C.
Jahangir Nagar
Jahangir Nagar is the former Mughal-era name of present-day Dhaka, given in honor of the emperor Jahangir.
-
D.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
E.
Ashoknagar
Ashoknagar is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its agricultural economy and regional trade.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c404e92c8190bd018673383f4534 |
completed | March 1, 2026, 10:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58b0be2c8190993a5b4592acf7d2 |
completed | March 8, 2026, 11:08 a.m. |
| NEDg | Description generation | batch_69ad5a3e7d008190870770ea16909a6a |
completed | March 8, 2026, 11:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad5ad5f50c81908541eb94bb1236b6 |
completed | March 8, 2026, 11:17 a.m. |
Created at: March 1, 2026, 7:59 p.m.