Triple
T7155223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean MARC |
E166790
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | KORMARC |
E27070
|
NE 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: KORMARC | Statement: [Korean MARC, relatedTo, KORMARC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KORMARC Context triple: [Korean MARC, relatedTo, KORMARC]
-
A.
KORMARC
chosen
KORMARC is the Korean implementation of the MARC bibliographic data format standard used for cataloging and exchanging library records in Korea.
-
B.
KMC
KMC is the commonly used abbreviation for Kirori Mal College, a prominent constituent college of the University of Delhi in India.
-
C.
KMC
KMC is the municipal governing body responsible for providing and managing civic services and infrastructure in Karachi, Pakistan.
-
D.
NORMARC
NORMARC is a Norwegian implementation of the MARC bibliographic metadata standard used by libraries to catalog and exchange information about their collections.
-
E.
CMARC
CMARC is the Chinese Machine-Readable Cataloging format, a localized variant of the MARC bibliographic standard used primarily in Chinese-language library cataloging systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e80c747c8190a017a2b1c3e78a3f |
completed | March 27, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8f42abc8190856210b8dea0a6de |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:47 p.m.