Triple
T15160703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panerai |
E362205
|
entity |
| Predicate | caseSizeCharacteristic |
P28652
|
FINISHED |
| Object | oversized cases |
—
|
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: oversized cases | Statement: [Panerai, caseSizeCharacteristic, oversized cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseSizeCharacteristic Context triple: [Panerai, caseSizeCharacteristic, oversized cases]
-
A.
sizeCategory
Indicates the relative size classification assigned to an entity compared to others (e.g., small, medium, large).
-
B.
sizeDescription
chosen
Indicates a relationship where one entity provides descriptive information about the size or scale of another entity.
-
C.
sizeStatus
Indicates the relative size condition or classification of one entity in relation to another or to a defined standard.
-
D.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
E.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060f2efc8190aa0eb5fb8d4ce085 |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:08 a.m.