Triple
T934950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Easter Bunny |
E20173
|
entity |
| Predicate | holidayRole |
P21750
|
FINISHED |
| Object | judging children’s behavior |
—
|
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: judging children’s behavior | Statement: [Easter Bunny, holidayRole, judging children’s behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holidayRole Context triple: [Easter Bunny, holidayRole, judging children’s behavior]
-
A.
holidayType
Indicates the specific category or kind of holiday associated with an event or date (e.g., public, religious, national, or personal).
-
B.
holidayAssociation
Indicates a relationship where one entity is connected to, themed around, or designated for a particular holiday.
-
C.
holidaySchedule
Indicates the planned dates, times, and durations during which holidays occur or are observed.
-
D.
holidayStatus
Indicates the current holiday-related state or condition associated with an entity, such as whether it is a holiday, non-holiday, or a specific holiday type.
-
E.
relatedHoliday
Indicates that there is an association or connection between two holidays, such as thematic, temporal, cultural, or contextual relatedness.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b363ea5c819098ec1d87f785bad4 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.