Triple
T22074860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Youth Test |
E545496
|
entity |
| Predicate | teaBreak |
P146537
|
FINISHED |
| Object | scheduled afternoon break |
—
|
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: scheduled afternoon break | Statement: [Youth Test, teaBreak, scheduled afternoon break]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teaBreak Context triple: [Youth Test, teaBreak, scheduled afternoon break]
-
A.
teaType
Indicates the specific variety or category of tea associated with an entity.
-
B.
teaCategory
Indicates that one item is classified as belonging to a particular category or type of tea.
-
C.
teaSeason
Indicates the season or time of year during which tea is typically grown, harvested, or most commonly consumed.
-
D.
teaCulture
Indicates the relationship in which practices, rituals, and social norms surrounding the preparation and consumption of tea are shared, expressed, or maintained.
-
E.
teaBrand
Indicates that one entity is a brand or producer associated with a particular type or product line of tea for the other entity.
- F. None of above. chosen
Provenance (4 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b1904881909a1769ce8be39e05 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
| PDg | Predicate description generation | batch_69e6fad59ef48190b62a2af636918a15 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:28 p.m.