Triple
T23418299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tara Brooch |
E560572
|
entity |
| Predicate | ornamentationExtent |
P80973
|
FINISHED |
| Object | almost entire surface decorated |
—
|
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: almost entire surface decorated | Statement: [Tara Brooch, ornamentationExtent, almost entire surface decorated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ornamentationExtent Context triple: [Tara Brooch, ornamentationExtent, almost entire surface decorated]
-
A.
ornamentationStyle
Indicates the decorative design or stylistic approach applied as ornamentation to an entity.
-
B.
decorativeComplexity
chosen
Indicates the degree or richness of ornamental detail or embellishment present in something.
-
C.
notableOrnamental
Indicates that something is recognized as a particularly significant or distinguished example of ornamental decoration or design.
-
D.
hasOrnamentation
Indicates that an entity possesses decorative features or embellishments applied to its surface or structure.
-
E.
adornedWith
Indicates that one entity is decorated, embellished, or ornamented by another entity.
- 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a5438ac08190a40a3d6402794699 |
completed | April 29, 2026, 6:29 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:39 p.m.