Triple
T8164194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorling Kindersley |
E190648
|
entity |
| Predicate | publishesInMultipleLanguages |
P35567
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dorling Kindersley, publishesInMultipleLanguages, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publishesInMultipleLanguages Context triple: [Dorling Kindersley, publishesInMultipleLanguages, true]
-
A.
isMultilingual
Indicates that an entity can understand and/or communicate in multiple languages.
-
B.
wroteInMultipleLanguages
Indicates that an entity authored written works using more than one language.
-
C.
presentedInLanguage
Indicates that something (such as content, information, or a work) is expressed or made available using a particular language.
-
D.
hasLanguages
chosen
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
languageOfAvailableEditions
Indicates the language in which the available editions of a work or resource are published.
- 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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4664fef881908b0dc7b158aca398 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:38 p.m.