Triple
T364446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jobs |
E7927
|
entity |
| Predicate | usedInLanguageCommunity |
P5924
|
FINISHED |
| Object | English-speaking world |
—
|
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: English-speaking world | Statement: [Jobs, usedInLanguageCommunity, English-speaking world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInLanguageCommunity Context triple: [Jobs, usedInLanguageCommunity, English-speaking world]
-
A.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
B.
usedInCommunity
chosen
Indicates that something is employed, practiced, or applied within a particular community or communal context.
-
C.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
D.
usedByCommunity
Indicates that something is utilized or adopted collectively by a particular community.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe6c1b4819083335e880c205ed6 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.