Triple
T1468123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KORMARC |
E27070
|
entity |
| Predicate | hasDataFields |
P28893
|
FINISHED |
| Object | 01X-9XX 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: 01X-9XX fields | Statement: [KORMARC, hasDataFields, 01X-9XX fields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDataFields Context triple: [KORMARC, hasDataFields, 01X-9XX fields]
-
A.
hasColumns
Indicates that one entity possesses or is characterized by a set of columns associated with it.
-
B.
hasCells
Indicates that an entity contains, is composed of, or is associated with one or more cells.
-
C.
hasFieldColor
Indicates that an entity possesses a field whose color is specified by another entity or value.
-
D.
hasFieldOfScalars
Indicates that one mathematical structure (typically a vector space or module) is defined over, and thus uses, a particular field as its scalars.
-
E.
hasMarketData
Indicates that an entity possesses or is associated with relevant market-related information or statistics.
- 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.