Triple
T36735294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biorn |
E907453
|
entity |
| Predicate | hasDiacriticsInVariant |
P2270
|
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: [Biorn, hasDiacriticsInVariant, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiacriticsInVariant Context triple: [Biorn, hasDiacriticsInVariant, true]
-
A.
hasUnicodeVariant
Indicates that one entity has an alternative representation or equivalent form in Unicode corresponding to the other entity.
-
B.
usesDiacritics
chosen
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
-
C.
hasVariantWithoutToneMarks
Indicates that one textual form is a variant of another in which all tone marks have been removed.
-
D.
usesDiacriticsFrom
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
-
E.
diacriticFunction
Indicates that a diacritic serves a particular role or effect in relation to the base character or linguistic unit it modifies.
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:12 p.m.