Triple
T33369106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panzer Kaserne, Böblingen, Germany |
E854434
|
entity |
| Predicate | hasPrimaryWorkingLanguageOnBase |
P78017
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Panzer Kaserne, Böblingen, Germany, hasPrimaryWorkingLanguageOnBase, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryWorkingLanguageOnBase Context triple: [Panzer Kaserne, Böblingen, Germany, hasPrimaryWorkingLanguageOnBase, English]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
hasPrimaryVernacularLanguageFamily
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
C.
hasPrimaryTraditionalLanguage
Indicates that one entity is the main or principal traditional language associated with another entity.
-
D.
hasPrimaryLanguageSubbranch
Indicates that one language subbranch is the main or principal subbranch associated with a given language or language family.
-
E.
hasPrimaryLanguageOfOperations
chosen
Indicates that an entity conducts its main activities or operations primarily using a specified language.
- 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_69f3496bda8c8190bfc8fade9d1b791c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a018f9c7cf88190adc5daf3806f2077 |
completed | May 11, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_6a018ca4e0e481908091f0c1f8a4c31b |
completed | May 11, 2026, 8 a.m. |
Created at: May 1, 2026, 1:35 a.m.