Triple
T25871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Union Flag |
E517
|
entity |
| Predicate | stripeColors |
P60
|
FINISHED |
| Object | red 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: red and white | Statement: [Grand Union Flag, stripeColors, red and white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stripeColors Context triple: [Grand Union Flag, stripeColors, red and white]
-
A.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
coinDenominationsInclude
Indicates that a set of coin denominations contains a particular denomination as one of its members.
-
C.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
D.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
E.
settlementType
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.