Triple
T8448395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William B. Breuer |
E199737
|
entity |
| Predicate | educationOrTraining |
P48900
|
FINISHED |
| Object | self-taught in military history |
—
|
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: self-taught in military history | Statement: [William B. Breuer, educationOrTraining, self-taught in military history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationOrTraining Context triple: [William B. Breuer, educationOrTraining, self-taught in military history]
-
A.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
B.
educationField
chosen
Indicates the academic or professional discipline in which an entity has been educated or trained.
-
C.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
D.
educationIndicator
Indicates that there is a measure or metric reflecting some aspect of educational status, performance, or outcomes associated with the entities.
-
E.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe445b7988190b53ae45070c70d1d |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.