Triple
T1559637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavarian Academy of Sciences and Humanities |
E33288
|
entity |
| Predicate | buildingLocatedAtStreetAddress |
P606
|
FINISHED |
| Object | Alfons-Goppel-Strasse 11 |
—
|
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: Alfons-Goppel-Strasse 11 | Statement: [Bavarian Academy of Sciences and Humanities, buildingLocatedAtStreetAddress, Alfons-Goppel-Strasse 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingLocatedAtStreetAddress Context triple: [Bavarian Academy of Sciences and Humanities, buildingLocatedAtStreetAddress, Alfons-Goppel-Strasse 11]
-
A.
streetAddress
chosen
Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
-
B.
streetLocation
Indicates that one entity is located on, along, or at a specific street associated with the other entity.
-
C.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
D.
boroughNumber
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
-
E.
streetAddressRange
Indicates the span of street address numbers (e.g., from a minimum to a maximum) that are associated with a particular street segment or location.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:27 p.m.