Triple
T7306899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaur |
E167994
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Lakhnauti
Lakhnauti is the medieval name of the historic city of Gaur, a major political and cultural center of the Bengal Sultanate in eastern India.
|
E689717
|
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: Lakhnauti | Statement: [Gaur, alsoKnownAs, Lakhnauti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakhnauti Context triple: [Gaur, alsoKnownAs, Lakhnauti]
-
A.
Rampurhat
Rampurhat is a town and important railway junction in the Birbhum district of West Bengal, India.
-
B.
Adityapur
Adityapur is a major industrial township in Jharkhand, India, known for its large concentration of manufacturing and engineering units.
-
C.
Krishnanagar
Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
-
D.
Jangipur
Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
-
E.
Santipur
Santipur is a historic town in West Bengal, India, renowned for its traditional handloom sarees and cultural heritage.
- 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: Lakhnauti Triple: [Gaur, alsoKnownAs, Lakhnauti]
Generated description
Lakhnauti is the medieval name of the historic city of Gaur, a major political and cultural center of the Bengal Sultanate in eastern India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakhnauti Target entity description: Lakhnauti is the medieval name of the historic city of Gaur, a major political and cultural center of the Bengal Sultanate in eastern India.
-
A.
Rampurhat
Rampurhat is a town and important railway junction in the Birbhum district of West Bengal, India.
-
B.
Adityapur
Adityapur is a major industrial township in Jharkhand, India, known for its large concentration of manufacturing and engineering units.
-
C.
Krishnanagar
Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
-
D.
Jangipur
Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
-
E.
Santipur
Santipur is a historic town in West Bengal, India, renowned for its traditional handloom sarees and cultural heritage.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebd7dcf88190b3e66bea327fc63d |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9061709f48190a9e198dac225aed4 |
completed | March 29, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_69c9069a60e88190be4b8c1dc1f1a3af |
completed | March 29, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9071da2c48190b3d50e460c312c67 |
completed | March 29, 2026, 11:03 a.m. |
Created at: March 27, 2026, 3:01 p.m.