Triple
T10552319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thousand Islands cruises |
E248981
|
entity |
| Predicate | languageOption |
P11734
|
FINISHED |
| Object | English commentary |
—
|
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 commentary | Statement: [Thousand Islands cruises, languageOption, English commentary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOption Context triple: [Thousand Islands cruises, languageOption, English commentary]
-
A.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
C.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
D.
languageProvision
chosen
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52710869c81909b6db1a190825bad |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:34 p.m.