Triple
T19451092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 15 series |
E486614
|
entity |
| Predicate | materialInProModels |
P104293
|
FINISHED |
| Object | titanium frame |
—
|
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: titanium frame | Statement: [iPhone 15 series, materialInProModels, titanium frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialInProModels Context triple: [iPhone 15 series, materialInProModels, titanium frame]
-
A.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
B.
featuresMaterialType
chosen
Indicates that an entity is characterized by or incorporates a specific type of material.
-
C.
usesMaterialBy
Indicates that one entity makes use of or employs a material that is provided, specified, or created by another entity.
-
D.
materialOptions
Indicates that there are one or more possible materials that can be chosen or applied in relation to a given entity or context.
-
E.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338db7c081908793f23592ebef6b |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.