Triple
T214296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MARC standards |
E4784
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | MARC 21 |
E4784
|
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: MARC 21 | Statement: [MARC standards, hasComponent, MARC 21]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MARC 21 Context triple: [MARC standards, hasComponent, MARC 21]
-
A.
MARC
MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
-
B.
MARC standards
chosen
MARC standards are a set of bibliographic data formats used worldwide to structure and exchange library catalog information in a consistent, machine-readable way.
-
C.
BIBFRAME
BIBFRAME (Bibliographic Framework) is a linked data model and standard developed by the Library of Congress to replace MARC for describing and sharing bibliographic information on the web.
-
D.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
-
E.
Library of Congress Subject Headings
Library of Congress Subject Headings is a comprehensive controlled vocabulary used by libraries worldwide to provide standardized subject access to cataloged materials.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c32ae208190a03d504ef43ea659 |
completed | Feb. 28, 2026, 3:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3441cc15c8190910b1b9e5dbb4910 |
completed | Feb. 28, 2026, 7:38 p.m. |
Created at: Feb. 28, 2026, 2:52 a.m.