Triple
T16777848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzuki Alto |
E407773
|
entity |
| Predicate | soldBy |
P7792
|
FINISHED |
| Object | Maruti Suzuki |
E406498
|
NE FINISHED |
How this triple was built (2 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: Maruti Suzuki | Statement: [Suzuki Alto, soldBy, Maruti Suzuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maruti Suzuki Context triple: [Suzuki Alto, soldBy, Maruti Suzuki]
-
A.
Maruti Suzuki
chosen
Maruti Suzuki is India’s largest automobile manufacturer, best known for producing affordable, mass-market passenger vehicles that dominate the country’s car market.
-
B.
Maruti
Maruti is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and protection.
-
C.
Tata Motors
Tata Motors is a major Indian multinational automotive manufacturer known for producing a wide range of passenger and commercial vehicles and for owning the luxury car brand Jaguar Land Rover.
-
D.
Toyota Sienta
The Toyota Sienta is a compact multi-purpose vehicle (MPV) known for its versatile three-row seating, sliding rear doors, and efficient urban-friendly design, popular in several Asian markets.
-
E.
Isuzu
Isuzu is a Japanese automotive manufacturer best known for producing commercial vehicles, pickup trucks, and diesel engines for global markets.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b212fc248190a8fe1124853bf16d |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab00cf708190a2562fa14d72a4df |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 5:22 a.m.