Triple
T13290189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMG Line |
E316541
|
entity |
| Predicate | doesNotNecessarilyInclude |
P72024
|
FINISHED |
| Object | full AMG engine upgrades |
—
|
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: full AMG engine upgrades | Statement: [AMG Line, doesNotNecessarilyInclude, full AMG engine upgrades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotNecessarilyInclude Context triple: [AMG Line, doesNotNecessarilyInclude, full AMG engine upgrades]
-
A.
doesNotNecessarily
chosen
Indicates that the specified condition, relationship, or outcome is not guaranteed to hold, even if other related conditions are true.
-
B.
doesNotSpecify
Indicates that the subject intentionally leaves some information, detail, or attribute undefined or unspecified with respect to the object.
-
C.
doesNotCover
Indicates that one entity fails to include, protect, or extend over another entity or area.
-
D.
doesNotFullyExplain
Indicates that one entity’s explanation of another entity, event, or situation is incomplete or insufficient to account for it fully.
-
E.
doesNotPrimarilyContain
Indicates that one entity does not have another entity as its main or predominant component, element, or content.
- F. None of above.
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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:27 p.m.