Triple
T12372104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AP exams |
E295027
|
entity |
| Predicate | scoreMeaning_1 |
P37395
|
FINISHED |
| Object | no recommendation |
—
|
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: no recommendation | Statement: [AP exams, scoreMeaning_1, no recommendation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoreMeaning_1 Context triple: [AP exams, scoreMeaning_1, no recommendation]
-
A.
ratingMeaning
chosen
Indicates the qualitative interpretation or significance associated with a given rating value in the relationship.
-
B.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
C.
firstScoreDescription
Indicates the textual description associated with an entity’s first or initial score.
-
D.
scoreScale
Indicates the scale or range on which a score or rating is expressed or measured.
-
E.
coScoredWith
Indicates that two or more entities received the same score or were evaluated with an identical scoring outcome in a shared context.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.