Triple
T6985644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum of the Future |
E161952
|
entity |
| Predicate | languageOfFacadeText |
P48899
|
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: [Museum of the Future, languageOfFacadeText, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFacadeText Context triple: [Museum of the Future, languageOfFacadeText, Arabic]
-
A.
languageOfInterface
Indicates the language used by or presented in a user interface.
-
B.
languageView
Indicates a relationship where one entity views, interprets, or presents another entity through the lens of a particular language or linguistic perspective.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageOfProduct
chosen
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
-
E.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbbd926c8190a8b60527bd553fa3 |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.