Triple
T29513471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Light |
E748722
|
entity |
| Predicate | settingTone |
P49759
|
FINISHED |
| Object | stark |
—
|
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: stark | Statement: [Light, settingTone, stark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingTone Context triple: [Light, settingTone, stark]
-
A.
haveTone
Indicates that an entity possesses or exhibits a particular tone, such as a specific attitude, mood, or quality of expression.
-
B.
contributesToTone
chosen
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
C.
inTonality
Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
-
D.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
E.
toneCategory
Indicates the tonal classification or type assigned to an entity, such as its pitch pattern, mood, or prosodic category.
- 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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 28, 2026, 4:34 p.m.