Triple
T32887975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schultheiss |
E841253
|
entity |
| Predicate | hasOriginalTitleFunction |
P195697
|
FINISHED |
| Object | local administrator |
—
|
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: local administrator | Statement: [Schultheiss, hasOriginalTitleFunction, local administrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalTitleFunction Context triple: [Schultheiss, hasOriginalTitleFunction, local administrator]
-
A.
hasOriginalTitleScript
Indicates that an entity’s original title is written or represented in a specific writing system or script.
-
B.
hasOriginalTitleMeaning
Indicates that an entity’s original title conveys or is associated with a particular meaning or interpretation.
-
C.
hasOriginalPaperTitle
Indicates that an entity (such as a publication or work) is associated with the title it originally had when first created or published.
-
D.
hasTitleInOriginalWork
Indicates that an entity holds a specific title or designation within its original work or source context.
-
E.
hasOriginalCountryTitle
Indicates that an entity is associated with the title it originally had in its country of origin.
- F. None of above. chosen
Provenance (4 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: May 1, 2026, 1:18 a.m.