Triple
T4404700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Hall (Library of Congress) |
E93699
|
entity |
| Predicate | decorativeProgramIncludes |
P34175
|
FINISHED |
| Object | allegorical murals |
—
|
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: allegorical murals | Statement: [Great Hall (Library of Congress), decorativeProgramIncludes, allegorical murals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decorativeProgramIncludes Context triple: [Great Hall (Library of Congress), decorativeProgramIncludes, allegorical murals]
-
A.
decorativeProgram
chosen
Indicates a relationship where a program or plan is created or used primarily for decorative, aesthetic, or ornamental purposes rather than functional ones.
-
B.
decorations
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
C.
programIncluded
Indicates that a particular program is contained within, or forms part of, another specified collection, package, or set of programs.
-
D.
decorationSystem
Indicates a system or method used to apply, manage, or organize decorative elements in or around an entity.
-
E.
decoration
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b35488d5b8819087370dd77249aefb |
completed | March 13, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.