Triple
T913057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franz Kafka Prize |
E19705
|
entity |
| Predicate | languageOfLaureates |
P17914
|
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: [Franz Kafka Prize, languageOfLaureates, multiple languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLaureates Context triple: [Franz Kafka Prize, languageOfLaureates, multiple languages]
-
A.
awardNameLanguage
Indicates the language in which the name of an award is expressed.
-
B.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
C.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
D.
roleInNobelPrize
Indicates the specific capacity or function an entity had in relation to a particular Nobel Prize (e.g., laureate, nominee, organization, or associated role).
-
E.
nobelPrizeRelated
Indicates that there is a connection or association between an entity and the Nobel Prize, such as receiving, being nominated for, or otherwise being significantly linked to 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.