Triple
T33812059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cros-ny-Cuirn |
E866561
|
entity |
| Predicate | hasScaleModelRepresentation |
P116650
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Cros-ny-Cuirn, hasScaleModelRepresentation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScaleModelRepresentation Context triple: [Cros-ny-Cuirn, hasScaleModelRepresentation, yes]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
scaleModelOf
chosen
Indicates that one entity is a scaled representation (larger or smaller but proportionally accurate) of another entity.
-
C.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
D.
hasScaleSize
Indicates that one entity possesses a scale characterized by a particular size or magnitude in relation to another entity or value.
-
E.
hasRealModel
Indicates that an abstract, theoretical, or simplified entity is associated with a corresponding concrete or physically instantiated model in the real world.
- 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_69f349911a8c81908478662194b23d8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: May 1, 2026, 1:46 a.m.