Triple
T147727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Rogers |
E3366
|
entity |
| Predicate | approachEmphasizes |
P31
|
FINISHED |
| Object | client’s subjective experience |
—
|
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: client’s subjective experience | Statement: [Carl Rogers, approachEmphasizes, client’s subjective experience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approachEmphasizes Context triple: [Carl Rogers, approachEmphasizes, client’s subjective experience]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
policyApproach
Indicates the strategy, method, or overall course of action adopted in creating, implementing, or managing a policy.
-
C.
strengthens
Indicates that one entity increases the power, effectiveness, or resilience of another.
-
D.
encourages
Indicates actively motivating, supporting, or giving confidence to another entity to pursue an action, behavior, or state.
-
E.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.