Triple
T14999085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Tanzania |
E374035
|
entity |
| Predicate | colourMeaningBlue |
P38846
|
FINISHED |
| Object | Indian Ocean and inland waters |
—
|
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: Indian Ocean and inland waters | Statement: [flag of Tanzania, colourMeaningBlue, Indian Ocean and inland waters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colourMeaningBlue Context triple: [flag of Tanzania, colourMeaningBlue, Indian Ocean and inland waters]
-
A.
blueStripeMeaning
Indicates that something has the meaning, symbolism, or significance associated specifically with a blue stripe.
-
B.
blueFieldMeaning
Indicates that a specified field or area is associated with the color blue, typically in appearance, status, or categorical designation.
-
C.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
D.
blueRepresents
chosen
Indicates that the color blue is used to symbolize, denote, or stand for a particular concept, state, or category in a given context.
-
E.
primaryColorSymbolism
Indicates how a primary color is symbolically associated with particular meanings, emotions, or concepts 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded71a5618819083ae96a79735ef98 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.