Triple
T20677450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narsinghgarh State |
E508196
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Narsinghgarh
Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
|
E1454510
|
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: Narsinghgarh | Statement: [Narsinghgarh State, capital, Narsinghgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narsinghgarh Context triple: [Narsinghgarh State, capital, Narsinghgarh]
-
A.
Ramgarh
Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
-
B.
Ramgarh
Ramgarh is a town in the Alwar district of Rajasthan, India, known for its historic forts, temples, and traditional Rajasthani culture.
-
C.
Jaisinghpur
Jaisinghpur is a town located in the Sultanpur district of the Indian state of Uttar Pradesh.
-
D.
Laxmangarh
Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
-
E.
Laxmangarh
Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
- 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: Narsinghgarh Triple: [Narsinghgarh State, capital, Narsinghgarh]
Generated description
Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Narsinghgarh Target entity description: Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
-
A.
Ramgarh
Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
-
B.
Ramgarh
Ramgarh is a town in the Alwar district of Rajasthan, India, known for its historic forts, temples, and traditional Rajasthani culture.
-
C.
Jaisinghpur
Jaisinghpur is a town located in the Sultanpur district of the Indian state of Uttar Pradesh.
-
D.
Laxmangarh
Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
-
E.
Laxmangarh
Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea24f288190928f828e5f567257 |
completed | April 21, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a090aeae39881909a35767b9b57eab4 |
completed | May 17, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_6a090fb735cc8190a1dfea82584b7675 |
completed | May 17, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a091010ef9c8190862283f739b7027b |
completed | May 17, 2026, 12:47 a.m. |
Created at: April 16, 2026, 11:44 a.m.