Triple
T15951940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TGV V150 |
E386837
|
entity |
| Predicate | testSectionAlignment |
P121101
|
FINISHED |
| Object | optimized for high speed |
—
|
LITERAL 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: optimized for high speed | Statement: [TGV V150, testSectionAlignment, optimized for high speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testSectionAlignment Context triple: [TGV V150, testSectionAlignment, optimized for high speed]
-
A.
testSectionHeight
Indicates that a specific test section has a particular height value or measurement.
-
B.
hasSectionLength
Indicates that an entity is associated with a specific length value for one of its sections.
-
C.
appliesToSectionOf
Indicates that something is relevant or applicable specifically to a particular section or subsection of a larger whole.
-
D.
isNamedSectionOf
Indicates that one entity is a specifically named section or subdivision that forms part of another entity.
-
E.
hasVerticalSection
Indicates that one entity possesses or includes a distinct vertical section or segment as part of its structure or representation.
- F. None of above. chosen
Provenance (4 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:53 a.m.