Triple
T23092265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio García |
E575789
|
entity |
| Predicate | mayBeWrittenWithoutDiacriticsAs |
P128884
|
FINISHED |
| Object | Antonio Garcia |
—
|
NE NERFINISHED |
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: Antonio Garcia | Statement: [Antonio García, mayBeWrittenWithoutDiacriticsAs, Antonio Garcia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeWrittenWithoutDiacriticsAs Context triple: [Antonio García, mayBeWrittenWithoutDiacriticsAs, Antonio Garcia]
-
A.
isTransliteratedWithoutDiacriticsInEnglish
chosen
Indicates that an entity’s name or term is represented in English letters without including any diacritical marks from the original script.
-
B.
canBeWrittenAsKana
Indicates that something (typically text or a term) is able to be represented using Japanese kana characters.
-
C.
usesDiacriticsFrom
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
-
D.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
E.
isWrittenWithoutSpace
Indicates that the referenced elements are written together as a single contiguous string, with no spaces between them.
- 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18dab3798819081b2b46a20751b2a |
completed | April 29, 2026, 4:48 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:57 p.m.