Triple
T16727444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maruti Suzuki |
E406498
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object | Maruti 800 |
E407773
|
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 800 | Statement: [Maruti Suzuki, notableModel, Maruti 800]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maruti 800 Context triple: [Maruti Suzuki, notableModel, Maruti 800]
-
A.
Maruti
Maruti is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and protection.
-
B.
WagonR
WagonR is a popular compact hatchback car in India known for its tall-boy design, spacious interior, and fuel efficiency.
-
C.
Maruti Suzuki
Maruti Suzuki is India’s largest automobile manufacturer, best known for producing affordable, mass-market passenger vehicles that dominate the country’s car market.
-
D.
Suzuki Alto
chosen
The Suzuki Alto is a long-running line of compact city cars known for their affordability, fuel efficiency, and popularity in markets worldwide.
-
E.
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.
- 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_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. |
Created at: April 10, 2026, 5:20 a.m.