Triple
T26987624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S.H.I.E.L.D. Academy |
E679775
|
entity |
| Predicate | notableCurriculumElement |
P64158
|
FINISHED |
| Object | field simulations |
—
|
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: field simulations | Statement: [S.H.I.E.L.D. Academy, notableCurriculumElement, field simulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCurriculumElement Context triple: [S.H.I.E.L.D. Academy, notableCurriculumElement, field simulations]
-
A.
notableCourse
chosen
Indicates that a course is particularly significant, distinguished, or noteworthy in relation to an entity (such as a person or institution).
-
B.
notableCourseType
Indicates that a course has a particular notable or distinguished type or classification (e.g., flagship, honors, or otherwise specially recognized).
-
C.
notableTeaching
Indicates that one entity is recognized for having taught, instructed, or educated another entity in a notable or significant way.
-
D.
teachingUnit
Indicates that one entity functions as an instructional or educational unit used for teaching another entity.
-
E.
notableStudentWork
Indicates that the subject has a student whose work is particularly notable or significant in relation to the subject.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff6074bcd4819090b72cd6209ff206 |
completed | May 9, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69ff600aba888190812a6e7eca0283b8 |
completed | May 9, 2026, 4:25 p.m. |
Created at: April 27, 2026, 6:49 a.m.