Triple
T148468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlborough Tapestries |
E3379
|
entity |
| Predicate | usesPerspective |
P854
|
FINISHED |
| Object | Baroque spatial composition |
—
|
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: Baroque spatial composition | Statement: [Marlborough Tapestries, usesPerspective, Baroque spatial composition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPerspective Context triple: [Marlborough Tapestries, usesPerspective, Baroque spatial composition]
-
A.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
B.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
C.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
-
D.
narrativePerspective
Indicates the point of view or vantage from which a narrative is told, specifying the relationship between the storyteller and the events being described.
-
E.
hasView
chosen
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ecb6f48190992c4c8ca908a81c |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.