Triple
T11444633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alwar district |
E271231
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Laxmangarh
Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
|
E933141
|
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: Laxmangarh | Statement: [Alwar district, contains, Laxmangarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laxmangarh Context triple: [Alwar district, contains, Laxmangarh]
-
A.
Laxmangarh
Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
-
B.
Karauli
Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
-
C.
Ramgarh
Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
-
D.
Bilaspuri
Bilaspuri is an Indo-Aryan language spoken primarily in the Bilaspur region of Himachal Pradesh in northern India.
-
E.
Lakhisarai
Lakhisarai is a town and administrative district headquarters in the eastern Indian state of Bihar, known for its historical significance and role as a regional commercial center.
- 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: Laxmangarh Triple: [Alwar district, contains, Laxmangarh]
Generated description
Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laxmangarh Target entity description: Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
-
A.
Laxmangarh
Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
-
B.
Karauli
Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
-
C.
Ramgarh
Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
-
D.
Bilaspuri
Bilaspuri is an Indo-Aryan language spoken primarily in the Bilaspur region of Himachal Pradesh in northern India.
-
E.
Lakhisarai
Lakhisarai is a town and administrative district headquarters in the eastern Indian state of Bihar, known for its historical significance and role as a regional commercial center.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8088a66f48190b2b4a56cd62097cf |
completed | April 9, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e7800ca881909c1816a74b3b8f19 |
completed | April 21, 2026, 2:57 a.m. |
| NEDg | Description generation | batch_69e6ef8fca248190bc2fdd8457258874 |
completed | April 21, 2026, 3:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e6f8ec88e88190bfa21c2d06d67bd8 |
completed | April 21, 2026, 4:11 a.m. |
Created at: April 8, 2026, 9:35 p.m.