Triple
T68151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Library of Congress Control Number |
E1358
|
entity |
| Predicate | hasCatalogingCode |
P508
|
FINISHED |
| Object | LCCN |
—
|
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: LCCN | Statement: [Library of Congress Control Number, hasCatalogingCode, LCCN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCatalogingCode Context triple: [Library of Congress Control Number, hasCatalogingCode, LCCN]
-
A.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
B.
hasDeweyDecimalClassification
Indicates that an item (such as a book or resource) is assigned a specific Dewey Decimal Classification number representing its subject area in a library system.
-
C.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
D.
codifiedIn
Indicates that something is formally recorded, defined, or established within a specific document, code, or legal/institutional text.
-
E.
numericCode
chosen
Indicates that an entity is associated with a specific numerical identifier or classification code.
- F. None of above.
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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea8cfd081908a26edad2473dde3 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.