Triple
T27952632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beam Drop |
E703468
|
entity |
| Predicate | hasSpatialAspect |
P149239
|
FINISHED |
| Object | outdoor site-specific installation |
—
|
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: outdoor site-specific installation | Statement: [Beam Drop, hasSpatialAspect, outdoor site-specific installation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpatialAspect Context triple: [Beam Drop, hasSpatialAspect, outdoor site-specific installation]
-
A.
spatialAspect
chosen
Indicates how something is positioned, oriented, or arranged in space relative to other entities or a reference frame.
-
B.
aspectRatio
Indicates the proportional relationship between an entity’s width and its height.
-
C.
typicalAspect
Indicates that something represents a characteristic or commonly occurring aspect of another thing or situation.
-
D.
hasSpatialResolution
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
E.
aspectRatioRangeAllowed
Indicates that only images or media whose aspect ratios fall within a specified minimum-to-maximum range are permitted.
- 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_69ef840c8b2c8190946ae9522774ba51 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 27, 2026, 7:25 p.m.