Triple
T34976648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château-Salins |
E1008693
|
entity |
| Predicate | hasSaltRelatedToponymy |
P186495
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Château-Salins, hasSaltRelatedToponymy, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSaltRelatedToponymy Context triple: [Château-Salins, hasSaltRelatedToponymy, yes]
-
A.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
B.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
C.
hasToponymicForm
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
D.
hasAlternativeToponymy
Indicates that an entity is associated with one or more alternative place names or toponyms used to refer to the same geographic location.
-
E.
hasReligiousToponym
Indicates that a place name is derived from or explicitly references a religious figure, concept, institution, or tradition.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:01 p.m.