Triple
T2788855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sussex |
E61876
|
entity |
| Predicate | colorVarietyCount |
P43593
|
FINISHED |
| Object | multiple color varieties |
—
|
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: multiple color varieties | Statement: [Sussex, colorVarietyCount, multiple color varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorVarietyCount Context triple: [Sussex, colorVarietyCount, multiple color varieties]
-
A.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
B.
hasColorOption
Indicates that an entity offers or supports a particular color as one of its selectable options.
-
C.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
-
D.
has32Varieties
Indicates that one entity possesses or includes exactly 32 distinct types, forms, or varieties of another entity.
-
E.
maxColorsOnScreen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 9:58 p.m.