Triple
T12343657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Udaipur district |
E294293
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Mavli
Mavli is a town in Rajasthan, India, known as a local transport and railway junction within the Udaipur district.
|
E987666
|
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: Mavli | Statement: [Udaipur district, containsTown, Mavli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mavli Context triple: [Udaipur district, containsTown, Mavli]
-
A.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
B.
Nandod
Nandod is the former name of the town now known as Rajpipla in the Indian state of Gujarat.
-
C.
Sawantwadi
Sawantwadi is a historic town in Maharashtra, India, known for its former royal palace, traditional wooden toys, and scenic location near the Goa border.
-
D.
Ulhasnagar
Ulhasnagar is a city in the Mumbai Metropolitan Region of Maharashtra, India, known for its large Sindhi community and extensive furniture and textile markets.
-
E.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
- 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: Mavli Triple: [Udaipur district, containsTown, Mavli]
Generated description
Mavli is a town in Rajasthan, India, known as a local transport and railway junction within the Udaipur district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mavli Target entity description: Mavli is a town in Rajasthan, India, known as a local transport and railway junction within the Udaipur district.
-
A.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
B.
Nandod
Nandod is the former name of the town now known as Rajpipla in the Indian state of Gujarat.
-
C.
Sawantwadi
Sawantwadi is a historic town in Maharashtra, India, known for its former royal palace, traditional wooden toys, and scenic location near the Goa border.
-
D.
Ulhasnagar
Ulhasnagar is a city in the Mumbai Metropolitan Region of Maharashtra, India, known for its large Sindhi community and extensive furniture and textile markets.
-
E.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f78a970819086beec3e4da8c49e |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b90779881909893d1e6877ce567 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64d15a97c81909046190f0d0fd986 |
completed | May 2, 2026, 7:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64e6d311c8190b851b89e394165d0 |
completed | May 2, 2026, 7:20 p.m. |
Created at: April 8, 2026, 9:53 p.m.