Triple
T3025634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medical College Admission Test |
E82568
|
entity |
| Predicate | totalScoreRange |
P16725
|
FINISHED |
| Object | 472–528 |
—
|
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: 472–528 | Statement: [Medical College Admission Test, totalScoreRange, 472–528]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalScoreRange Context triple: [Medical College Admission Test, totalScoreRange, 472–528]
-
A.
mathScoreRange
Indicates the range of possible or observed math scores associated with an entity.
-
B.
finalScore
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
-
C.
totalPointsScored
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
-
D.
scoreScale
chosen
Indicates the scale or range on which a score or rating is expressed or measured.
-
E.
topTryScorer
Indicates that the subject is the player who scored the highest number of tries in a given competition, season, or 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_69ad8b1fb34081908c1b873e2b7273e1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9abc78b48190a5283e7407a78fe7 |
completed | March 8, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69ad961c430c8190ac48f2e3c7e7c649 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.