Triple
T5871333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Localish |
E130521
|
entity |
| Predicate | contentTone |
P29502
|
FINISHED |
| Object | feel-good stories |
—
|
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: feel-good stories | Statement: [Localish, contentTone, feel-good stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentTone Context triple: [Localish, contentTone, feel-good stories]
-
A.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
B.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
C.
textContent
Indicates that one entity is the textual content or written material contained within another entity.
-
D.
moralTone
Indicates the evaluative moral quality or ethical character expressed in or associated with an action, statement, or situation.
-
E.
primaryTone
chosen
Indicates the main or dominant emotional or stylistic quality characterizing something, in contrast to any secondary or supporting tones.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.