Triple
T34096934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frederick Herzberg |
E874453
|
entity |
| Predicate | hygieneFactorsInclude |
P36515
|
FINISHED |
| Object | salary |
—
|
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: salary | Statement: [Frederick Herzberg, hygieneFactorsInclude, salary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hygieneFactorsInclude Context triple: [Frederick Herzberg, hygieneFactorsInclude, salary]
-
A.
hasCleanlinessLevel
Indicates the degree or state of cleanliness associated with an entity.
-
B.
evaluationCriteriaInclude
chosen
Indicates that certain criteria are part of, or explicitly included in, the set of standards used to evaluate something.
-
C.
qualifyingFeaturesInclude
Indicates that certain qualifying features are part of, or included within, a specified set of features associated with an entity or condition.
-
D.
considersFactor
Indicates that one entity takes another entity into account as a factor when forming a judgment, decision, or evaluation.
-
E.
includesMeasures
Indicates that one entity contains, specifies, or encompasses particular measures associated with another entity or context.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70c6153e48190879589fa9eab790f |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:53 a.m.