Triple
T1894803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 25th Annual Putnam County Spelling Bee |
E41953
|
entity |
| Predicate | typicalActCount |
P12050
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [The 25th Annual Putnam County Spelling Bee, typicalActCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalActCount Context triple: [The 25th Annual Putnam County Spelling Bee, typicalActCount, 2]
-
A.
numberOfActs
chosen
Indicates the total count of discrete acts or actions associated with a given entity or event.
-
B.
typicalNumberOfSelectedFilms
Indicates the usual or average number of films that are chosen or selected in a given context or process.
-
C.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
D.
typicalCasting
Indicates that one entity is the usual or standard casting choice for portraying another entity (such as a role, character, or type).
-
E.
typicalNumberOfNominees
Indicates the usual or standard count of nominees associated with something, such as an award, position, or selection process.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.