Triple
T8414751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Pro with M1 |
E198705
|
entity |
| Predicate | availableInSize |
P82040
|
FINISHED |
| Object | 11-inch |
—
|
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: 11-inch | Statement: [iPad Pro with M1, availableInSize, 11-inch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: availableInSize Context triple: [iPad Pro with M1, availableInSize, 11-inch]
-
A.
sizeStatus
Indicates the relative size condition or classification of one entity in relation to another or to a defined standard.
-
B.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
C.
sizeDescription
Indicates a relationship where one entity provides descriptive information about the size or scale of another entity.
-
D.
sizeCategory
Indicates the relative size classification assigned to an entity compared to others (e.g., small, medium, large).
-
E.
includesSizeRange
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e443a08190983d9a0a61e0f781 |
completed | March 31, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 6:06 p.m.