Triple
T34230721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DeWit |
E878181
|
entity |
| Predicate | hasMeaningInDutch |
P187777
|
FINISHED |
| Object | the white |
—
|
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: the white | Statement: [DeWit, hasMeaningInDutch, the white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningInDutch Context triple: [DeWit, hasMeaningInDutch, the white]
-
A.
meaningInDutch
chosen
Indicates that one entity expresses the meaning or translation of another entity in the Dutch language.
-
B.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
C.
hasMeaningInEstonian
Indicates that something possesses a particular meaning or interpretation in the Estonian language.
-
D.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
-
E.
hasNameInDutch
Indicates that an entity is associated with a specific name or label expressed in the Dutch language.
- 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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff0d80c0dc81909fbd12285c7a45c0 |
completed | May 9, 2026, 10:33 a.m. |
| PD | Predicate disambiguation | batch_69ff0cd03e78819094895058f925fbfa |
completed | May 9, 2026, 10:30 a.m. |
Created at: May 1, 2026, 1:56 a.m.