Triple
T31301686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Did Something Bad |
E798228
|
entity |
| Predicate | hasDarkAesthetic |
P172953
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [I Did Something Bad, hasDarkAesthetic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDarkAesthetic Context triple: [I Did Something Bad, hasDarkAesthetic, true]
-
A.
isDark
Indicates that an entity possesses a low level of lightness or brightness, making it visually dark.
-
B.
hasDarkerTone
Indicates that one entity possesses a color or shade that is visually darker than that of another entity.
-
C.
hasDarkLyrics
Indicates that the associated content contains lyrics with dark, grim, or disturbing themes.
-
D.
hasDarkSkyDesignation
Indicates that a place has been officially recognized with a Dark Sky designation for its exceptional nighttime darkness and efforts to reduce light pollution.
-
E.
hasColorAesthetic
Indicates that one entity possesses or is characterized by a particular color-based visual style or aesthetic.
- F. None of above. chosen
Provenance (4 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b2d9aad88190a445f8f591cb19fc |
completed | May 3, 2026, 2:28 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: April 29, 2026, 9:14 p.m.