Triple
T22036728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crystal Labyrinth Mirror Maze |
E544228
|
entity |
| Predicate | targetAudienceAgeGroup |
P10804
|
FINISHED |
| Object | children and adults |
—
|
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: children and adults | Statement: [Crystal Labyrinth Mirror Maze, targetAudienceAgeGroup, children and adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudienceAgeGroup Context triple: [Crystal Labyrinth Mirror Maze, targetAudienceAgeGroup, children and adults]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
C.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
D.
ageGroupIndicated
Indicates that a specific age range or category is identified or assigned to an entity.
-
E.
primarySpeakersAgeGroup
Indicates the age range category to which the main or primary speakers in a context belong.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f1f95c8190a324c84313cd91ee |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:25 p.m.