Triple
T23012734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G-Force |
E572950
|
entity |
| Predicate | designScope |
P150657
|
FINISHED |
| Object | chassis |
—
|
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: chassis | Statement: [G-Force, designScope, chassis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designScope Context triple: [G-Force, designScope, chassis]
-
A.
designAspect
Indicates that one entity represents a particular design-related feature, characteristic, or consideration of another entity.
-
B.
designCheck
Indicates that an entity performs a review or verification of a design to ensure it meets specified requirements or standards.
-
C.
designModel
Indicates that one entity creates, specifies, or defines the structure or behavior of another entity as a model or blueprint.
-
D.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
-
E.
designDescription
Indicates that an entity has a textual explanation or summary of its design, structure, or intended configuration.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e202a481908d7a2f00a12229a0 |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
| PDg | Predicate description generation | batch_69ef538b29c081908fa56ee35a1dcee7 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:51 p.m.