Triple
T19500689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiat Chrysler Automobiles |
E487893
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | SRT |
—
|
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: SRT | Statement: [Fiat Chrysler Automobiles, brand, SRT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SRT Context triple: [Fiat Chrysler Automobiles, brand, SRT]
-
A.
SRT
SRT was the former name of Toronto’s Line 3 Scarborough, an elevated light rapid transit line that operated in the city’s eastern suburbs.
-
B.
SRT
SRT is the national state-owned railway operator of Thailand, responsible for the country’s intercity and commuter rail services.
-
C.
SRT
SRT is a South Korean high-speed rail service that operates on major routes including those connecting through Daejeon.
-
D.
SRT
chosen
SRT is a high-performance trim level of Jeep vehicles, featuring upgraded powertrains, sport-tuned components, and enhanced styling.
-
E.
SRTMU
SRTMU is a public state university in Nanded, Maharashtra, India, named after Swami Ramanand Teerth and serving the Marathwada region with various undergraduate and postgraduate programs.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350ce7cc819086d77bbd9cd52b53 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.