Triple
T32887887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schultze |
E841249
|
entity |
| Predicate | hasOriginalMeaningRole |
P12511
|
FINISHED |
| Object | local official responsible for collecting dues |
—
|
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 official responsible for collecting dues | Statement: [Schultze, hasOriginalMeaningRole, local official responsible for collecting dues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalMeaningRole Context triple: [Schultze, hasOriginalMeaningRole, local official responsible for collecting dues]
-
A.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
B.
hasOriginalTitleMeaning
Indicates that an entity’s original title conveys or is associated with a particular meaning or interpretation.
-
C.
originalMeaning
chosen
Indicates that something retains or conveys its initial, intended sense or significance, as opposed to a later or altered interpretation.
-
D.
hasOriginalCharacter
Indicates that an entity includes, features, or is associated with an original character distinct from pre-existing or canonical characters.
-
E.
hasTranslatedMeaning
Indicates that one entity expresses the meaning of another entity in a different language through translation.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:18 a.m.