Triple
T691703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Test of English as a Foreign Language |
E13805
|
entity |
| Predicate | scoreScale |
P16725
|
FINISHED |
| Object | 0–30 per section |
—
|
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: 0–30 per section | Statement: [Test of English as a Foreign Language, scoreScale, 0–30 per section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoreScale Context triple: [Test of English as a Foreign Language, scoreScale, 0–30 per section]
-
A.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
B.
scoreScaleVerbal
Indicates the verbal description or label corresponding to a particular score or score range on a scale.
-
C.
isScoreFor
Indicates that one value represents the score or result associated with a particular entity, event, or performance.
-
D.
scoreScaleAnalyticalWriting
Indicates the scoring scale or range used to evaluate and rate analytical writing performance.
-
E.
gradeRank
Indicates the relative academic standing or position of an entity within a graded or ranked group based on performance or scores.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0aebde88190a49d421477713103 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d221d38819083c0adda81f59b07 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49dc20880819085fa60dc1851f9dc |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:36 p.m.