Triple
T23915970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finisterre–Huon languages |
E602081
|
entity |
| Predicate | areLessUsedFor |
P89202
|
FINISHED |
| Object | formal education |
—
|
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: formal education | Statement: [Finisterre–Huon languages, areLessUsedFor, formal education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areLessUsedFor Context triple: [Finisterre–Huon languages, areLessUsedFor, formal education]
-
A.
usedLessIn
chosen
Indicates that one entity is used with a lower frequency or intensity compared to another entity.
-
B.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
C.
isSometimesUsedFor
Indicates that something serves a particular purpose or function on some occasions, but not consistently or exclusively.
-
D.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
E.
isLessCommonSince
Indicates that the frequency or prevalence of one entity has decreased relative to another entity or to its own past occurrence from a specified point in time.
- 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_69e2953a187081908346a9f36e85fc98 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ce9917808190ad66a4e276a24b3d |
completed | April 29, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:40 p.m.