Triple
T20391358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameron |
E498091
|
entity |
| Predicate | modelDesignation |
P8607
|
FINISHED |
| Object | unknown Terminator model |
—
|
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: unknown Terminator model | Statement: [Cameron, modelDesignation, unknown Terminator model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelDesignation Context triple: [Cameron, modelDesignation, unknown Terminator model]
-
A.
manufacturerDesignation
Indicates that a specific designation, code, or model identifier has been assigned by the manufacturer to the referenced product or item.
-
B.
systemDesignation
Indicates that an entity has been assigned a specific formal label or identifier within a defined system or framework.
-
C.
robotModelDesignation
Indicates the specific model identifier or designation assigned to a robot.
-
D.
modelNumber
chosen
Indicates that one entity is the specific model identifier or code assigned to another entity (such as a product or device).
-
E.
vendorDesignation
Indicates that one entity assigns or recognizes a specific vendor status, label, or role for another entity within a business or procurement context.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790f8d9c819093038f6bb6f47a92 |
completed | April 20, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:28 a.m.