Triple
T16528560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hinjawadi |
E401501
|
entity |
| Predicate | nearTo |
P350
|
FINISHED |
| Object |
Baner
Baner is a rapidly developing residential and commercial suburb in the western part of Pune, Maharashtra, known for its IT offices, eateries, and proximity to major tech hubs.
|
E1218773
|
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: Baner | Statement: [Hinjawadi, nearTo, Baner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baner Context triple: [Hinjawadi, nearTo, Baner]
-
A.
Bangar
Bangar is a coastal municipality in the province of La Union in the Philippines, known for its handwoven textiles and agricultural products.
-
B.
Shingora
Shingora is a film featuring Indian actress and model Persis Khambatta, known for her distinctive screen presence and international appeal.
-
C.
Banshiwala
Banshiwala is a Bengali novel by acclaimed writer Shirshendu Mukhopadhyay, known for its evocative storytelling and exploration of human relationships.
-
D.
Balwa
Balwa is a municipality-level city located in Nepal's Madhesh Province.
-
E.
Bhalla
Bhalla is an Indian surname commonly found among people of Punjabi and North Indian origin.
- 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: Baner Triple: [Hinjawadi, nearTo, Baner]
Generated description
Baner is a rapidly developing residential and commercial suburb in the western part of Pune, Maharashtra, known for its IT offices, eateries, and proximity to major tech hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baner Target entity description: Baner is a rapidly developing residential and commercial suburb in the western part of Pune, Maharashtra, known for its IT offices, eateries, and proximity to major tech hubs.
-
A.
Bangar
Bangar is a coastal municipality in the province of La Union in the Philippines, known for its handwoven textiles and agricultural products.
-
B.
Shingora
Shingora is a film featuring Indian actress and model Persis Khambatta, known for her distinctive screen presence and international appeal.
-
C.
Banshiwala
Banshiwala is a Bengali novel by acclaimed writer Shirshendu Mukhopadhyay, known for its evocative storytelling and exploration of human relationships.
-
D.
Balwa
Balwa is a municipality-level city located in Nepal's Madhesh Province.
-
E.
Bhalla
Bhalla is an Indian surname commonly found among people of Punjabi and North Indian origin.
- 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_69e32ed57be481908625d4c5aab0940c |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608efd0c81908e64419bd74eb285 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a0062cbe9048190823db47a42dac26a |
completed | May 10, 2026, 10:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00635f57c08190ad915082b00b0f88 |
completed | May 10, 2026, 10:52 a.m. |
Created at: April 10, 2026, 5:14 a.m.