Triple
T23499665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Automatic Train Operation |
E571804
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | ATO |
—
|
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: ATO | Statement: [Automatic Train Operation, abbreviation, ATO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ATO Context triple: [Automatic Train Operation, abbreviation, ATO]
-
A.
ATO
ATO is the commonly used abbreviation for the Federal Aviation Administration’s Air Traffic Organization, which manages and oversees air traffic control services in the United States.
-
B.
ATO
ATO is Australia’s principal revenue collection agency responsible for administering the federal tax system and related superannuation laws.
-
C.
ATO
chosen
ATO (Automatic Train Operation) is a railway control system that automates key driving functions of trains, such as acceleration, braking, and stopping accuracy, to improve safety, efficiency, and service reliability.
-
D.
AUT
AUT is a major New Zealand university based in Auckland, known for its focus on applied research, innovation, and industry-aligned education.
-
E.
AUT
AUT is a leading Iranian engineering and technology university, widely recognized for its strong research output and rigorous academic 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8fb71c08190a30500b3f63a9ce6 |
completed | April 29, 2026, 6:45 a.m. |
Created at: April 17, 2026, 6:06 p.m.