Triple
T5007419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Styx |
E112530
|
entity |
| Predicate | dimensions_km |
P60807
|
FINISHED |
| Object | approximately 16 × 9 × 8 |
—
|
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: approximately 16 × 9 × 8 | Statement: [Styx, dimensions_km, approximately 16 × 9 × 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensions_km Context triple: [Styx, dimensions_km, approximately 16 × 9 × 8]
-
A.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
B.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
C.
widthKilometres
Indicates the measurement of how wide something is, expressed in kilometres.
-
D.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
E.
dimensionNote
Indicates that there is an explanatory note or annotation specifically about the dimensions or measurements associated with an entity or relationship.
- F. None of above. chosen
Provenance (4 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:35 p.m.