Triple
T11087767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cleopatra Beach (Marsa Matruh) |
E262165
|
entity |
| Predicate | languageUsedAtDestination |
P48682
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Cleopatra Beach (Marsa Matruh), languageUsedAtDestination, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAtDestination Context triple: [Cleopatra Beach (Marsa Matruh), languageUsedAtDestination, Arabic]
-
A.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageUsedInTourism
chosen
Indicates that a particular language is used for communication and services within tourism activities or contexts.
-
E.
hasOfficialLanguageOfSurroundingCountry
Indicates that an entity uses as its official language the same language that is official in the country surrounding 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799c5008081908f59612243fa4f7a |
completed | April 9, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.