Triple
T2192247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Men in Red |
E49887
|
entity |
| Predicate | colorReference |
P18898
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [Men in Red, colorReference, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorReference Context triple: [Men in Red, colorReference, red]
-
A.
colorReferenceExplains
Indicates that one color reference serves to clarify, define, or provide explanatory information about another color-related element or notation.
-
B.
hasColorReference
chosen
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another entity.
-
C.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
-
E.
colorTheory
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.