Triple
T16727448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maruti Suzuki |
E406498
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object |
Dzire
Dzire is a popular compact sedan produced by Maruti Suzuki for the Indian automotive market, known for its fuel efficiency and affordability.
|
E1232047
|
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: Dzire | Statement: [Maruti Suzuki, notableModel, Dzire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dzire Context triple: [Maruti Suzuki, notableModel, Dzire]
-
A.
WagonR
WagonR is a popular compact hatchback car in India known for its tall-boy design, spacious interior, and fuel efficiency.
-
B.
Maruti
Maruti is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and protection.
-
C.
Honda Vezel
The Honda Vezel is a subcompact crossover SUV produced by Honda, known for its versatile interior, fuel-efficient powertrains, and urban-friendly design.
-
D.
Tata Harrier
The Tata Harrier is a mid-size SUV from Tata Motors known for its bold design, spacious cabin, and strong road presence in the Indian market.
-
E.
Ertiga
The Ertiga is a popular compact multi-purpose vehicle (MPV) produced by Maruti Suzuki, known for its practicality, fuel efficiency, and family-friendly seating.
- 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: Dzire Triple: [Maruti Suzuki, notableModel, Dzire]
Generated description
Dzire is a popular compact sedan produced by Maruti Suzuki for the Indian automotive market, known for its fuel efficiency and affordability.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dzire Target entity description: Dzire is a popular compact sedan produced by Maruti Suzuki for the Indian automotive market, known for its fuel efficiency and affordability.
-
A.
WagonR
WagonR is a popular compact hatchback car in India known for its tall-boy design, spacious interior, and fuel efficiency.
-
B.
Maruti
Maruti is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and protection.
-
C.
Honda Vezel
The Honda Vezel is a subcompact crossover SUV produced by Honda, known for its versatile interior, fuel-efficient powertrains, and urban-friendly design.
-
D.
Tata Harrier
The Tata Harrier is a mid-size SUV from Tata Motors known for its bold design, spacious cabin, and strong road presence in the Indian market.
-
E.
Ertiga
The Ertiga is a popular compact multi-purpose vehicle (MPV) produced by Maruti Suzuki, known for its practicality, fuel efficiency, and family-friendly seating.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38748f538819097de1fdee9b42f34 |
completed | April 18, 2026, 1:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a519a89081909456bb6fc25d9234 |
completed | May 10, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a00a5c4e934819088db49d81be154c3 |
completed | May 10, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a6b84d288190aeccb06745146b80 |
completed | May 10, 2026, 3:39 p.m. |
Created at: April 10, 2026, 5:20 a.m.