Triple
T1342722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyperion |
E28501
|
entity |
| Predicate | dimension_km |
P3633
|
FINISHED |
| Object | 360 × 280 × 225 |
—
|
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: 360 × 280 × 225 | Statement: [Hyperion, dimension_km, 360 × 280 × 225]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimension_km Context triple: [Hyperion, dimension_km, 360 × 280 × 225]
-
A.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
B.
dimension
chosen
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
C.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
D.
depthMetresApprox
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
-
E.
distance
Indicates the spatial separation or length between two points, objects, or locations.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c2174d048190a6e9380df302265f |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef3e8fc8190ac9a1ba9b5879483 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.