Triple
T5926384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marathwada |
E131820
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Hingoli
Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
|
E569427
|
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: Hingoli | Statement: [Marathwada, hasMajorCity, Hingoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hingoli Context triple: [Marathwada, hasMajorCity, Hingoli]
-
A.
Buldhana
Buldhana is a district in the Indian state of Maharashtra known for its Marathi-speaking population and use of the Varhadi dialect.
-
B.
Sangli
Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
-
C.
Ratnagiri
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
-
D.
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.
-
E.
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.
- 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: Hingoli Triple: [Marathwada, hasMajorCity, Hingoli]
Generated description
Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hingoli Target entity description: Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
-
A.
Buldhana
Buldhana is a district in the Indian state of Maharashtra known for its Marathi-speaking population and use of the Varhadi dialect.
-
B.
Sangli
Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
-
C.
Ratnagiri
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
-
D.
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.
-
E.
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.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c038542e548190b335df9a948c8490 |
completed | March 22, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c124fda1848190894b51d45f2b0a7a |
completed | March 23, 2026, 11:33 a.m. |
| NEDg | Description generation | batch_69c128c384008190b6c11709b2d2eee9 |
completed | March 23, 2026, 11:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c129005930819095e2f4b296201611 |
completed | March 23, 2026, 11:50 a.m. |
Created at: March 22, 2026, 4 p.m.