Triple
T4713773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .sm |
E104580
|
entity |
| Predicate | sldExample |
P1259
|
FINISHED |
| Object | example.sm |
—
|
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: example.sm | Statement: [.sm, sldExample, example.sm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sldExample Context triple: [.sm, sldExample, example.sm]
-
A.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
B.
hasExample
chosen
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
C.
geographicalRepresentation
Indicates that one entity serves as a geographic depiction, model, or mapping of another entity’s location, area, or spatial characteristics.
-
D.
preservedExample
Indicates that an example instance has been kept intact or maintained in its original state for future reference or use.
-
E.
isUsedToIllustrate
Indicates that one entity serves as an example or demonstration to clarify, explain, or represent another entity.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd680beb508190b3d74e20e1c64405 |
completed | March 20, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69bd621ddcd88190903288566f5e5dab |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.