Triple
T2682262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law School Admission Test |
E57398
|
entity |
| Predicate | writingSampleScored |
P42223
|
FINISHED |
| Object | no |
—
|
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 | Statement: [Law School Admission Test, writingSampleScored, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSampleScored Context triple: [Law School Admission Test, writingSampleScored, no]
-
A.
scoreScaleAnalyticalWriting
Indicates the scoring scale or range used to evaluate and rate analytical writing performance.
-
B.
scoreIncrementAnalyticalWriting
Indicates an increase in a subject’s score specifically attributable to their analytical writing performance or improvement.
-
C.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
D.
writingForm
Indicates the specific script, notation, or written representation used to express a piece of language or content.
-
E.
written
Indicates that one entity has created or authored a text, document, or written work involving or about another entity.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda2dc5788190b4b83cb9ed08266c |
completed | March 7, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:54 p.m.