Triple
T7146789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cieplice Śląskie-Zdrój |
E166588
|
entity |
| Predicate | hasFormerNameLanguage |
P52208
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Cieplice Śląskie-Zdrój, hasFormerNameLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerNameLanguage Context triple: [Cieplice Śląskie-Zdrój, hasFormerNameLanguage, German]
-
A.
formerName
Indicates that an entity was previously known by a different name in the past.
-
B.
languageOfHistoricName
chosen
Indicates the language in which a historic or former name of an entity is expressed.
-
C.
hasHistoricNameVariant
Indicates that an entity has an alternative name that was used in a historical period or past context.
-
D.
formerLanguage
Indicates that one entity was previously the language of another entity but is no longer in that role.
-
E.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7d4f3388190941f03fd80b0c223 |
completed | March 27, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.