Triple
T35633646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huebner |
E1029658
|
entity |
| Predicate | isOftenAnglicizedFrom |
P135924
|
FINISHED |
| Object | Hübner |
—
|
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: Hübner | Statement: [Huebner, isOftenAnglicizedFrom, Hübner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenAnglicizedFrom Context triple: [Huebner, isOftenAnglicizedFrom, Hübner]
-
A.
isOftenAmericanizedFormOf
Indicates that one term is a version of another term that has been adapted into common American usage, typically in spelling, form, or style.
-
B.
hasLaterNameInEnglish
Indicates that an entity is known by a different English name at a later time or in a subsequent context.
-
C.
isSometimesUsedAsVariantOf
Indicates that one entity is occasionally employed as an alternative or substitute form of another entity, but not as its primary or standard version.
-
D.
romanizationVariantOf
chosen
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
-
E.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:05 p.m.