Triple
T4485603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Decision Points |
E107229
|
entity |
| Predicate | lcClassification |
P2387
|
FINISHED |
| Object | E902 .B88 2010 |
—
|
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: E902 .B88 2010 | Statement: [Decision Points, lcClassification, E902 .B88 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lcClassification Context triple: [Decision Points, lcClassification, E902 .B88 2010]
-
A.
libraryOfCongressClassification
Indicates that one entity is assigned a Library of Congress Classification code that organizes it within the Library of Congress subject-based cataloging system.
-
B.
hasLCClassification
chosen
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
C.
classificationByUS
Indicates a relationship where an entity is assigned a category, status, or type according to a classification system defined or used by the United States.
-
D.
classified
Indicates that one entity has assigned another entity to a specific category, group, or type based on defined criteria.
-
E.
doctrineClassification
Indicates how a particular doctrine is categorized or classified within a defined system of doctrinal types.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:59 p.m.