Triple
T14022096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fin the Whale |
E337359
|
entity |
| Predicate | characterColor |
P60
|
FINISHED |
| Object | black and white |
—
|
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: black and white | Statement: [Fin the Whale, characterColor, black and white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterColor Context triple: [Fin the Whale, characterColor, black and white]
-
A.
leadCharacterColor
Indicates that one entity is the primary character and the other specifies the color associated with that lead character.
-
B.
accentColor
Indicates the color used as a highlight or emphasis within a visual design or interface.
-
C.
colorFieldCharacteristic
Indicates that a field or attribute is characterized or distinguished by a specific color.
-
D.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
E.
colorIndicates
Indicates that a particular color serves as a sign, marker, or signal conveying specific information or status about something.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f3d87b88190b038d334f4965369 |
completed | April 14, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69de05a802ac819090604025aae6a4d5 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:19 p.m.