Triple
T11431795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanded Lok Sabha constituency |
E270901
|
entity |
| Predicate | assemblySegment |
P63908
|
FINISHED |
| Object |
Bhokar
Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
|
E924979
|
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: Bhokar | Statement: [Nanded Lok Sabha constituency, assemblySegment, Bhokar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bhokar Context triple: [Nanded Lok Sabha constituency, assemblySegment, Bhokar]
-
A.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
-
B.
Dhundhari
Dhundhari is an Indo-Aryan language spoken primarily in and around Jaipur and adjoining regions of Rajasthan, India.
-
C.
Chakia
Chakia is a town in the East Champaran district of the Indian state of Bihar, known primarily as a local administrative and market center for the surrounding rural region.
-
D.
Sachkhere
Sachkhere is a town in western Georgia known as a local administrative and economic center in the Imereti region.
-
E.
Sakesar
Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
- 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: Bhokar Triple: [Nanded Lok Sabha constituency, assemblySegment, Bhokar]
Generated description
Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bhokar Target entity description: Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
-
A.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
-
B.
Dhundhari
Dhundhari is an Indo-Aryan language spoken primarily in and around Jaipur and adjoining regions of Rajasthan, India.
-
C.
Chakia
Chakia is a town in the East Champaran district of the Indian state of Bihar, known primarily as a local administrative and market center for the surrounding rural region.
-
D.
Sachkhere
Sachkhere is a town in western Georgia known as a local administrative and economic center in the Imereti region.
-
E.
Sakesar
Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c30d788190b0c939b33de89277 |
completed | April 9, 2026, 8:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b8e212088190b611333d5de05757 |
completed | April 20, 2026, 5:25 a.m. |
| NEDg | Description generation | batch_69e5c28f24108190aa48ca90440d6d7f |
completed | April 20, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c474d2c88190882a55ae6621daef |
completed | April 20, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:35 p.m.