Triple
T8715196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haferlschuhe |
E206875
|
entity |
| Predicate | hasTypicalCut |
P84047
|
FINISHED |
| Object | low-cut |
—
|
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: low-cut | Statement: [Haferlschuhe, hasTypicalCut, low-cut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCut Context triple: [Haferlschuhe, hasTypicalCut, low-cut]
-
A.
hasCut
Indicates that one entity has made or possesses a cut in, on, or through another entity.
-
B.
isCutInto
Indicates that one entity is divided or separated into pieces or segments that become the other entity.
-
C.
commonCut
Indicates that two or more entities share at least one identical segment or portion that has been cut or divided in the same way.
-
D.
hasAlternateCut
Indicates that an entity has an alternative edited version or cut, distinct from its primary or original form.
-
E.
hasTypicalSide
Indicates that one entity is the usual or characteristic side (e.g., lateral aspect) 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd807cc819090b58caf285b397a |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c40c54819093d174a4203f9515 |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.