Triple
T11784033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-29 |
E280223
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | T-29D |
E280223
|
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: T-29D | Statement: [T-29, hasVariant, T-29D]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-29D Context triple: [T-29, hasVariant, T-29D]
-
A.
T-29
chosen
T-29 is a U.S. Air Force military trainer aircraft variant of the Convair 240 series used primarily for navigation and radar training.
-
B.
T-25 Universal
The T-25 Universal is a Brazilian-designed military trainer aircraft widely used for basic flight instruction and pilot training.
-
C.
T-2 Buckeye
The T-2 Buckeye is an American-built jet trainer aircraft widely used for advanced pilot training, notably by the U.S. Navy and several foreign air forces.
-
D.
T-10
T-10 is the station code for Nihonbashi Station on Tokyo Metro’s Tozai Line in central Tokyo.
-
E.
T-68
The T-68 was an early generation light rail tram used on the Manchester Metrolink system in the UK before being superseded by newer models.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a585795c8190aa8a5edf0d99b47f |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f166c735008190a73dd74dbcddd182 |
completed | April 29, 2026, 2:02 a.m. |
Created at: April 8, 2026, 9:42 p.m.