Triple
T20158079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Oldesloe |
E491628
|
entity |
| Predicate | hasNamePrefixMeaning |
P27718
|
FINISHED |
| Object | spa town |
—
|
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: spa town | Statement: [Bad Oldesloe, hasNamePrefixMeaning, spa town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamePrefixMeaning Context triple: [Bad Oldesloe, hasNamePrefixMeaning, spa town]
-
A.
hasPrefixMeaning
chosen
Indicates that one entity serves as a semantic prefix of another, contributing a specific meaning to the start of the second entity.
-
B.
hasBaseNameMeaning
Indicates that an entity’s base name carries or is associated with a particular meaning.
-
C.
hasGivenNameMeaning
Indicates that a given name carries a particular meaning or semantic interpretation.
-
D.
hasNameMeaningRelation
Indicates that there is a relationship between an entity and a name that conveys or encodes a particular meaning or significance.
-
E.
hasMeaningAsPatronymicMarker
Indicates that something functions as a marker showing that a name is derived from a father’s or ancestor’s personal name (i.e., it serves as a patronymic indicator).
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.