Triple
T26160275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waitangi Bay |
E660088
|
entity |
| Predicate | hasLanguageUsedInArea |
P29819
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Waitangi Bay, hasLanguageUsedInArea, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageUsedInArea Context triple: [Waitangi Bay, hasLanguageUsedInArea, English]
-
A.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
B.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
C.
usedForLanguageSpokenIn
Indicates that something (such as a resource, tool, or medium) is used for expressing or communicating a language that is spoken in a particular place or region.
-
D.
linguisticStatusOfArea
Indicates the linguistic status or condition that characterizes a particular geographic area.
-
E.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 26, 2026, 8:29 p.m.