Triple
T123889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institute Professor at MIT |
E2504
|
entity |
| Predicate | mayHaveReducedTeachingLoad |
P4924
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Institute Professor at MIT, mayHaveReducedTeachingLoad, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveReducedTeachingLoad Context triple: [Institute Professor at MIT, mayHaveReducedTeachingLoad, true]
-
A.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
B.
hasTeachingAuthority
Indicates that one entity possesses the recognized power or right to teach, instruct, or provide formal education to another entity or within a specific context.
-
C.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
D.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
E.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a2573ce0ac8190b49fb31d3d475bf9 |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564a54948190ba30bee858173b27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.