Triple
T768927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanford Tree |
E16236
|
entity |
| Predicate | costumeUpdateFrequency |
P16914
|
FINISHED |
| Object | new costume typically created each year |
—
|
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: new costume typically created each year | Statement: [Stanford Tree, costumeUpdateFrequency, new costume typically created each year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeUpdateFrequency Context triple: [Stanford Tree, costumeUpdateFrequency, new costume typically created each year]
-
A.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
B.
haveDistinctCostume
Indicates that the entities each possess a costume that is different from the others’ costumes.
-
C.
performedFrequency
chosen
Indicates how often an action or activity is carried out within a given time period.
-
D.
awardedFrequency
Indicates how often an award or recognition is given within a specified time period.
-
E.
meetingFrequency
Indicates how often a meeting or recurring gathering takes place over a given period.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a701e584819095905cf74d33e11c |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.