Triple
T37604056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Garrison |
E935599
|
entity |
| Predicate | previousJobTitle |
P2939
|
FINISHED |
| Object | 3rd grade teacher |
—
|
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: 3rd grade teacher | Statement: [Mr. Garrison, previousJobTitle, 3rd grade teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousJobTitle Context triple: [Mr. Garrison, previousJobTitle, 3rd grade teacher]
-
A.
professionalTitleAfterCompletion
Indicates that an entity is granted or holds a specific professional title as a result of successfully completing a particular program, course, or qualification.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
previousTitle
chosen
Indicates that one title held or used by an entity directly preceded another title in sequence or time.
-
D.
previousOffice
Indicates that one office or position was held immediately before another in a sequence of offices.
-
E.
previousDepartment
Indicates that an entity was formerly associated with or belonged to a specified department before a change occurred.
- 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffecdcbac4819093b725a7dbe0e61b |
completed | May 10, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69ffec3633288190adbbd84e277708dc |
completed | May 10, 2026, 2:23 a.m. |
Created at: May 3, 2026, 4:18 p.m.