Triple
T35740613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sit at the Table |
E1033021
|
entity |
| Predicate | critiquesBehavior |
P141337
|
FINISHED |
| Object | sitting on the sidelines in professional contexts |
—
|
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: sitting on the sidelines in professional contexts | Statement: [Sit at the Table, critiquesBehavior, sitting on the sidelines in professional contexts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: critiquesBehavior Context triple: [Sit at the Table, critiquesBehavior, sitting on the sidelines in professional contexts]
-
A.
criticizesBehaviorOf
chosen
Indicates that one entity expresses disapproval of, or points out faults in, the behavior or conduct of another entity.
-
B.
aimsToCritique
Indicates an intention to analyze and point out faults, limitations, or weaknesses in something.
-
C.
typeOfCriticism
Indicates that one entity is a specific kind or category of criticism directed at another entity or subject.
-
D.
critiquesConcept
Indicates that one entity analyzes, evaluates, or challenges the ideas or principles represented by another entity.
-
E.
criticismReason
Indicates that one entity criticizes another entity specifically because of the stated reason.
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.