Triple
T37460108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Instructor Razuvious |
E930895
|
entity |
| Predicate | encounterStyle |
P188666
|
FINISHED |
| Object | multi-add control encounter |
—
|
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: multi-add control encounter | Statement: [Instructor Razuvious, encounterStyle, multi-add control encounter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encounterStyle Context triple: [Instructor Razuvious, encounterStyle, multi-add control encounter]
-
A.
encounterFrequency
Indicates how often two entities come into contact or interact with each other over a given period.
-
B.
encounterLocation
Indicates the place or setting where two or more entities meet, interact, or come into contact.
-
C.
checkInStyle
Indicates that an entity arrives or registers at a place or event in a notably fashionable or impressive manner.
-
D.
settingEncounter
Indicates that an encounter or interaction is taking place within a particular setting or environment.
-
E.
approachStyle
Indicates the manner or strategy with which one entity moves toward, engages with, or initiates interaction with another entity or target.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbacaea12c8190a4c99e64335f0e7e |
completed | May 6, 2026, 9:03 p.m. |
Created at: May 3, 2026, 4:17 p.m.