Triple
T30339099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NIM master |
E771698
|
entity |
| Predicate | roleInNIM |
P199725
|
FINISHED |
| Object | central control point |
—
|
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: central control point | Statement: [NIM master, roleInNIM, central control point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInNIM Context triple: [NIM master, roleInNIM, central control point]
-
A.
roleInClass
Indicates the specific function, position, or responsibility an entity holds within a particular class or group.
-
B.
roleWithinCollege
Indicates the specific position, function, or capacity an entity holds within a particular college.
-
C.
courseRole
Indicates the specific function or position an individual holds within a course, such as student, instructor, or assistant.
-
D.
campusRole
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
-
E.
roleInInstitutions
Indicates that an entity holds or has held a specific role, position, or function within one or more institutions.
- 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff5285ed74819097e6e2a9084a079a |
completed | May 9, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69ff51fbe28881908ac8417dff9db81a |
completed | May 9, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69ff528536d481909caefe52fcd8aaa7 |
completed | May 9, 2026, 3:28 p.m. |
Created at: April 29, 2026, 7:55 p.m.