Triple
T7322630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thane |
E168787
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object |
Mumbra
Mumbra is a densely populated suburban area in the Thane district of Maharashtra, India, known for its largely Muslim population and rapid urban growth.
|
E659474
|
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: Mumbra | Statement: [Thane, hasSuburb, Mumbra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mumbra Context triple: [Thane, hasSuburb, Mumbra]
-
A.
Vikhroli
Vikhroli is a suburban neighborhood in Mumbai known for its residential areas, industrial estates, and proximity to major transport links.
-
B.
Kurla
Kurla is a densely populated suburban neighborhood in Mumbai, India, known as a major residential, commercial, and transport hub of the city.
-
C.
Thane
Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
-
D.
Chembur
Chembur is a prominent suburban neighborhood in eastern Mumbai known for its residential areas, connectivity, and growing commercial and industrial presence.
-
E.
Viman Nagar
Viman Nagar is a prominent residential and commercial neighborhood in Pune, India, known for its proximity to the airport, IT parks, shopping malls, and educational institutions.
- 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: Mumbra Triple: [Thane, hasSuburb, Mumbra]
Generated description
Mumbra is a densely populated suburban area in the Thane district of Maharashtra, India, known for its largely Muslim population and rapid urban growth.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mumbra Target entity description: Mumbra is a densely populated suburban area in the Thane district of Maharashtra, India, known for its largely Muslim population and rapid urban growth.
-
A.
Vikhroli
Vikhroli is a suburban neighborhood in Mumbai known for its residential areas, industrial estates, and proximity to major transport links.
-
B.
Kurla
Kurla is a densely populated suburban neighborhood in Mumbai, India, known as a major residential, commercial, and transport hub of the city.
-
C.
Thane
Thane is a major city in western India known for its numerous lakes and its proximity to Mumbai.
-
D.
Chembur
Chembur is a prominent suburban neighborhood in eastern Mumbai known for its residential areas, connectivity, and growing commercial and industrial presence.
-
E.
Viman Nagar
Viman Nagar is a prominent residential and commercial neighborhood in Pune, India, known for its proximity to the airport, IT parks, shopping malls, and educational institutions.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0446628819093e96236f1aa4a9b |
completed | March 27, 2026, 9:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa7bfe248190a5def09d6941e114 |
completed | March 28, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69c7fea82f98819091b19b267261a8cc |
completed | March 28, 2026, 4:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ff5a17408190bddc197fc9d9299c |
completed | March 28, 2026, 4:18 p.m. |
Created at: March 27, 2026, 3:03 p.m.