Triple
T36507435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She No Longer Weeps |
E899505
|
entity |
| Predicate | workLanguageRegion |
P145769
|
FINISHED |
| Object | Anglophone Africa |
—
|
NE NERFINISHED |
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: Anglophone Africa | Statement: [She No Longer Weeps, workLanguageRegion, Anglophone Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageRegion Context triple: [She No Longer Weeps, workLanguageRegion, Anglophone Africa]
-
A.
subjectLanguageRegion
chosen
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
-
B.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
D.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
E.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
- 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:10 p.m.