Triple
T8437691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finley High School |
E199269
|
entity |
| Predicate | hasPossibleGrades |
P83364
|
FINISHED |
| Object | 9–12 |
—
|
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: 9–12 | Statement: [Finley High School, hasPossibleGrades, 9–12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPossibleGrades Context triple: [Finley High School, hasPossibleGrades, 9–12]
-
A.
hasGrades
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
-
B.
hasMaximumGrade
Indicates that an entity possesses the highest possible grade or score within a defined grading or evaluation system.
-
C.
hasNoGrades
Indicates that an entity does not possess any recorded grades or evaluations.
-
D.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
E.
hasGradeSystem
Indicates that one entity uses, follows, or is governed by a particular grading or evaluation system defined by 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:08 p.m.