Triple
T1366046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kavli Prize |
E30005
|
entity |
| Predicate | languageOfOfficialMaterial |
P19280
|
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: [Kavli Prize, languageOfOfficialMaterial, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOfficialMaterial Context triple: [Kavli Prize, languageOfOfficialMaterial, English]
-
A.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
B.
languageOfOfficialEditions
chosen
Indicates the language in which the official editions or versions of a work, document, or publication are produced or authorized.
-
C.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
D.
languageOfOfficialWebsite
Indicates the language in which an entity’s official website is primarily written or presented.
-
E.
additionalOfficialLanguage
Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.