Triple
T16529196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lohegaon |
E401518
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Wagholi
Wagholi is a rapidly developing suburban area near Pune, Maharashtra, known for its residential complexes, proximity to the IT hubs, and growing infrastructure.
|
E1223656
|
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: Wagholi | Statement: [Lohegaon, locatedNear, Wagholi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wagholi Context triple: [Lohegaon, locatedNear, Wagholi]
-
A.
Dalgaon
Dalgaon is a town and administrative center located in the Darrang district of the northeastern Indian state of Assam.
-
B.
Vadgaon Maval
Vadgaon Maval is a town in Maharashtra, India, known as a local hub within the Pune district’s Maval region.
-
C.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
D.
Navalgund
Navalgund is a town in the Indian state of Karnataka known for its traditional handloom cotton and silk sarees, especially the distinctive Navalgund durries.
-
E.
Warora
Warora is a town in Maharashtra, India, known historically for its coal mining and industrial activities within the Chandrapur district.
- 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: Wagholi Triple: [Lohegaon, locatedNear, Wagholi]
Generated description
Wagholi is a rapidly developing suburban area near Pune, Maharashtra, known for its residential complexes, proximity to the IT hubs, and growing infrastructure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wagholi Target entity description: Wagholi is a rapidly developing suburban area near Pune, Maharashtra, known for its residential complexes, proximity to the IT hubs, and growing infrastructure.
-
A.
Dalgaon
Dalgaon is a town and administrative center located in the Darrang district of the northeastern Indian state of Assam.
-
B.
Vadgaon Maval
Vadgaon Maval is a town in Maharashtra, India, known as a local hub within the Pune district’s Maval region.
-
C.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
D.
Navalgund
Navalgund is a town in the Indian state of Karnataka known for its traditional handloom cotton and silk sarees, especially the distinctive Navalgund durries.
-
E.
Warora
Warora is a town in Maharashtra, India, known historically for its coal mining and industrial activities within the Chandrapur district.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed625208190a68b879266b05b3f |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007da0867881908ad9391d6d4cdebb |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007e4df09081909f8d9485ed85d5b0 |
completed | May 10, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007ebd75c081908ff382d3548ca620 |
completed | May 10, 2026, 12:49 p.m. |
Created at: April 10, 2026, 5:14 a.m.