Triple
T20146361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washim district |
E491311
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Malegaon (Washim)
Malegaon (Washim) is a town located in the Washim district of Maharashtra, India.
|
E1414775
|
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: Malegaon (Washim) | Statement: [Washim district, hasTown, Malegaon (Washim)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malegaon (Washim) Context triple: [Washim district, hasTown, Malegaon (Washim)]
-
A.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
-
B.
Hingoli
Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
-
C.
Gondia
Gondia is a district in the Indian state of Maharashtra, known for its rice production and proximity to forests and wildlife reserves.
-
D.
Chandrapur
Chandrapur is a district in the eastern part of Maharashtra, India, known for its coal mining industry, forests, and wildlife, including the Tadoba-Andhari Tiger Reserve.
-
E.
Latur
Latur is a city in the Marathwada region of western India known for its agricultural economy and for being the epicenter of a devastating earthquake in 1993.
- 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: Malegaon (Washim) Triple: [Washim district, hasTown, Malegaon (Washim)]
Generated description
Malegaon (Washim) is a town located in the Washim district of Maharashtra, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Malegaon (Washim) Target entity description: Malegaon (Washim) is a town located in the Washim district of Maharashtra, India.
-
A.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
-
B.
Hingoli
Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
-
C.
Gondia
Gondia is a district in the Indian state of Maharashtra, known for its rice production and proximity to forests and wildlife reserves.
-
D.
Chandrapur
Chandrapur is a district in the eastern part of Maharashtra, India, known for its coal mining industry, forests, and wildlife, including the Tadoba-Andhari Tiger Reserve.
-
E.
Latur
Latur is a city in the Marathwada region of western India known for its agricultural economy and for being the epicenter of a devastating earthquake in 1993.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679e43a48190b3a5da5710b07ff7 |
completed | April 20, 2026, 5:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08346b8d7c819091e112e391ab1b58 |
completed | May 16, 2026, 9:10 a.m. |
| NEDg | Description generation | batch_6a08366132148190a316f28e027664eb |
completed | May 16, 2026, 9:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08370f25c4819085da226ded7ae658 |
completed | May 16, 2026, 9:21 a.m. |
Created at: April 11, 2026, 11:33 p.m.