Triple
T5716898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American College Testing |
E126044
|
entity |
| Predicate | scoreRangeComposite |
P16725
|
FINISHED |
| Object | 1–36 |
—
|
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: 1–36 | Statement: [American College Testing, scoreRangeComposite, 1–36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoreRangeComposite Context triple: [American College Testing, scoreRangeComposite, 1–36]
-
A.
scoreUsedFor
Indicates that a particular score or rating is used for a specific purpose, decision, or downstream process.
-
B.
scoreScale
chosen
Indicates the scale or range on which a score or rating is expressed or measured.
-
C.
coScoredWith
Indicates that two or more entities received the same score or were evaluated with an identical scoring outcome in a shared context.
-
D.
rankRange
Indicates that an entity’s rank falls within a specified minimum and maximum range.
-
E.
scoringType
Indicates the method or criteria by which performance, outcomes, or results are evaluated and assigned a score in a given 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c47f4c81909e6849c3be3e951c |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:46 p.m.