Triple
T20601727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theresienwiese U-Bahn station |
E506196
|
entity |
| Predicate | hasAdditionalSignageLanguage |
P97618
|
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: [Theresienwiese U-Bahn station, hasAdditionalSignageLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdditionalSignageLanguage Context triple: [Theresienwiese U-Bahn station, hasAdditionalSignageLanguage, English]
-
A.
hasAdditionalLanguageOfSignage
chosen
Indicates that an entity has signage presented in one or more additional languages beyond the primary language used.
-
B.
officialLanguageOfSignage
Indicates that a particular language is the one officially used on public signs and signage within a given place or context.
-
C.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
D.
tertiaryLanguageOfSignage
Indicates that a language is used as the third-most prominent language on signage in a given context or location.
-
E.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa20f5c881909265ce7d96efc487 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.