Triple
T263456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fireside chats on banking crisis |
E5801
|
entity |
| Predicate | hasTargetEmotion |
P2340
|
FINISHED |
| Object | reduce fear |
—
|
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: reduce fear | Statement: [Fireside chats on banking crisis, hasTargetEmotion, reduce fear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetEmotion Context triple: [Fireside chats on banking crisis, hasTargetEmotion, reduce fear]
-
A.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
B.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
C.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
D.
designedToEvoke
chosen
Indicates that something was intentionally created or arranged in order to elicit a particular reaction, feeling, or response from an audience or observer.
-
E.
hasConnotation
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to 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_69a258dd8ea08190ac554a1cc8dfd8c3 |
completed | Feb. 28, 2026, 2:54 a.m. |
| NER | Named-entity recognition | batch_69a25d8e809881908a58c9a4e3ba07c3 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.