Triple
T20305976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anjaneya |
E505609
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Maruti |
—
|
NE NERFINISHED |
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 | Statement: [Anjaneya, hasName, Maruti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maruti Context triple: [Anjaneya, hasName, Maruti]
-
A.
Maruti
chosen
Maruti is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and protection.
-
B.
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.
-
C.
Maruti 800
The Maruti 800 is a compact, affordable hatchback that became one of India’s most iconic and best-selling cars, widely credited with revolutionizing personal transportation in the country.
-
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.
Maruti Gypsy
The Maruti Gypsy is a compact, rugged off-road SUV produced by Maruti Suzuki in India, widely used by civilians, law enforcement, and the military for its durability and 4x4 capability.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6773f8f688190b616f972b9bbb28e |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:18 a.m.