Triple
T7775263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loewenstein |
E221373
|
entity |
| Predicate | hasNotableVariantSpelling |
P457
|
FINISHED |
| Object | Loewenstein without umlaut substitution |
—
|
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: Loewenstein without umlaut substitution | Statement: [Loewenstein, hasNotableVariantSpelling, Loewenstein without umlaut substitution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableVariantSpelling Context triple: [Loewenstein, hasNotableVariantSpelling, Loewenstein without umlaut substitution]
-
A.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
B.
hasTypicalSpelling
Indicates that one form is the standard or commonly accepted spelling of another form.
-
C.
hasVariantReadingsWith
Indicates a relationship where two textual items are linked because they exhibit differing or alternative readings of (typically) the same underlying content.
-
D.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
E.
hasOfficialNameVariant
Indicates that an entity has an alternative official form or version of its name.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 3:45 p.m.