Triple
T3398307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Al |
E71583
|
entity |
| Predicate | representsColors |
P60
|
FINISHED |
| Object | crimson |
—
|
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: crimson | Statement: [Big Al, representsColors, crimson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsColors Context triple: [Big Al, representsColors, crimson]
-
A.
nationalColorsRepresented
Indicates that the national colors of an entity are visibly included or symbolically expressed in another entity or context.
-
B.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
C.
originalColors
Indicates that something retains or is associated with its initial, unaltered set of colors.
-
D.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
E.
blueRepresents
Indicates that the color blue is used to symbolize, denote, or stand for a particular concept, state, or category in a given context.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8c5816881909f91e6e9b81d29e3 |
completed | March 8, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.