Triple
T37918044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Sangster |
E945876
|
entity |
| Predicate | hasToneAround |
P124796
|
FINISHED |
| Object | darkly comic situations |
—
|
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: darkly comic situations | Statement: [Frank Sangster, hasToneAround, darkly comic situations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToneAround Context triple: [Frank Sangster, hasToneAround, darkly comic situations]
-
A.
hasToneAroundEvents
chosen
Indicates that one entity expresses a particular emotional or evaluative tone in relation to certain events.
-
B.
haveTone
Indicates that an entity possesses or exhibits a particular tone, such as a specific attitude, mood, or quality of expression.
-
C.
hasToneFunction
Indicates that one entity serves a specific tonal or harmonic function in relation to another entity within a musical context.
-
D.
hasEndingTone
Indicates that something concludes with a particular tone, mood, or intonational quality.
-
E.
hasTonalityShift
Indicates a change in the tonal quality, mood, or key within a piece or segment, marking a shift from one tonality to another.
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 3, 2026, 4:20 p.m.