Triple
T24193828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liam O'Leary |
E599772
|
entity |
| Predicate | hasRegionOfCommonUse |
P908
|
FINISHED |
| Object | Ireland |
—
|
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: Ireland | Statement: [Liam O'Leary, hasRegionOfCommonUse, Ireland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionOfCommonUse Context triple: [Liam O'Leary, hasRegionOfCommonUse, Ireland]
-
A.
hasTypicalUsageRegion
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
B.
usedInRegion
chosen
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
C.
usedInAllRegionsOf
Indicates that something is utilized or applied in every region within a specified scope or system.
-
D.
hasNotableUsageRegion
Indicates that something is prominently or distinctively used within a particular geographic region.
-
E.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e24947948190b609a39a2b8828ad |
completed | April 29, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.