Triple
T32794356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferry laws on primary education |
E838716
|
entity |
| Predicate | appliesToAgeRange |
P177536
|
FINISHED |
| Object | approximately 6 to 13 years |
—
|
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 6 to 13 years | Statement: [Ferry laws on primary education, appliesToAgeRange, approximately 6 to 13 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToAgeRange Context triple: [Ferry laws on primary education, appliesToAgeRange, approximately 6 to 13 years]
-
A.
supportsAgeRange
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
-
B.
hasApproximateAgeRange
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
-
C.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
D.
focusesOnAgeRange
chosen
Indicates that something is specifically directed toward, concerned with, or tailored to a particular age range.
-
E.
hasProtagonistAgeRange
Indicates that a work’s main character falls within a specified age range.
- 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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fee0b2da3c8190a3519d0564f2f32d |
completed | May 9, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69fee05b315c819081dfcbfb15273487 |
completed | May 9, 2026, 7:20 a.m. |
Created at: May 1, 2026, 1:14 a.m.