Triple
T27008338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chronicler of the Winds |
E680308
|
entity |
| Predicate | hasAfricanSetting |
P161771
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chronicler of the Winds, hasAfricanSetting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAfricanSetting Context triple: [Chronicler of the Winds, hasAfricanSetting, true]
-
A.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
B.
countryOfSetting
Indicates the country in which the setting or context of something (such as a story, event, or work) takes place.
-
C.
hasApproximateAfricanFrequency
Indicates that an entity occurs in Africa with a frequency that is estimated or approximate rather than precisely measured.
-
D.
isPanAfricanSymbol
Indicates that something functions as a symbol representing Pan-African identity, unity, or solidarity across African peoples and the African diaspora.
-
E.
usesPanAfricanColors
Indicates that one entity employs or incorporates the Pan-African colors (typically red, black, green, and sometimes yellow) in relation to another entity.
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621d4667081909d0008559850bc10 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 27, 2026, 7:02 a.m.