Triple
T18294314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Locarno Classification |
E438191
|
entity |
| Predicate | numberOfSubclasses |
P289
|
FINISHED |
| Object | approximately 219 |
—
|
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 219 | Statement: [Locarno Classification, numberOfSubclasses, approximately 219]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubclasses Context triple: [Locarno Classification, numberOfSubclasses, approximately 219]
-
A.
hasMultipleSubclasses
Indicates that a class or category is related to more than one distinct subclass within a hierarchy.
-
B.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
C.
numberOfDicotSubclasses
Indicates the count of distinct dicot subclasses associated with or contained within a given entity.
-
D.
subclassOf
Indicates that one class is a more specific type of another class, inheriting its characteristics as a subset of it.
-
E.
numberOfChildren
chosen
Indicates the total count of children that an entity has.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5010205bc8190a32fe731ead3d988 |
completed | April 19, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.