Triple
T2229859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skytrax Airline of the Year 2003 |
E48738
|
entity |
| Predicate | languageOfSurveys |
P33549
|
FINISHED |
| Object | multiple languages |
—
|
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: multiple languages | Statement: [Skytrax Airline of the Year 2003, languageOfSurveys, multiple languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfSurveys Context triple: [Skytrax Airline of the Year 2003, languageOfSurveys, multiple languages]
-
A.
languageOfAssessment
Indicates that a specified language is used as the medium of assessment (e.g., for tests, evaluations, or examinations) for a given entity.
-
B.
languageOfRecords
Indicates the language in which the records are written or maintained.
-
C.
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.
-
D.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
E.
languageOfCommunications
chosen
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc069e0ac8190bcda8cba9f5c7a5d |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.