Triple
T269206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satisfaction |
E5589
|
entity |
| Predicate | hasBehavioralConsequence |
P812
|
FINISHED |
| Object | increased loyalty |
—
|
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: increased loyalty | Statement: [Satisfaction, hasBehavioralConsequence, increased loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBehavioralConsequence Context triple: [Satisfaction, hasBehavioralConsequence, increased loyalty]
-
A.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
conducts
Indicates that an entity organizes, directs, or carries out an activity, operation, or process involving another entity.
-
D.
hasConnotation
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
-
E.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25db00ed48190be6f598807265356 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.