Triple
T1468119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KORMARC |
E27070
|
entity |
| Predicate | hasFieldLength |
P28891
|
FINISHED |
| Object | variable-length fields |
—
|
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: variable-length fields | Statement: [KORMARC, hasFieldLength, variable-length fields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldLength Context triple: [KORMARC, hasFieldLength, variable-length fields]
-
A.
hasMinimumLength
Indicates that the length of an entity (such as a sequence, string, or collection) is greater than or equal to a specified minimum value.
-
B.
isFeatureLength
Indicates that something (typically a film or video) has a duration long enough to be considered a full-length, standard feature.
-
C.
hasFieldExtensionDegree
Indicates that one field is an extension of another and specifies the degree (dimension as a vector space) of this extension.
-
D.
hasFieldColor
Indicates that an entity possesses a field whose color is specified by another entity or value.
-
E.
hasNameLengthCategory
Indicates that an entity is associated with a classification describing the length of its name (e.g., short, medium, long).
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5d70a948190b50a6c1b36abc740 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c55508948190922aee3230a4323e |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8:01 p.m.