Triple
T8597600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eyrie Bay |
E203589
|
entity |
| Predicate | hasPrimaryLanguageOfMaps |
P83252
|
FINISHED |
| Object | English |
—
|
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 | Statement: [Eyrie Bay, hasPrimaryLanguageOfMaps, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfMaps Context triple: [Eyrie Bay, hasPrimaryLanguageOfMaps, English]
-
A.
hasPrimaryLanguage1
chosen
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
C.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
D.
hasRepresentativeLanguage
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46cacbe88190b95beeedc9f480b0 |
completed | March 31, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cc454504448190aaad2af8b17357cd |
completed | March 31, 2026, 10:05 p.m. |
Created at: March 30, 2026, 6:24 p.m.