Triple
T3876379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neue Nationalgalerie |
E92510
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tiergarten |
E106564
|
NE 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: Tiergarten | Statement: [Neue Nationalgalerie, locatedIn, Tiergarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiergarten Context triple: [Neue Nationalgalerie, locatedIn, Tiergarten]
-
A.
Tiergarten
chosen
Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
-
B.
Hofgarten
The Hofgarten is a historic Renaissance-style court garden in central Munich, known for its arcades, pavilions, and role as a popular public park and cultural venue.
-
C.
Schillerpark
Schillerpark is a historic public park in Berlin known for its expansive lawns, tree-lined paths, and role as a popular recreational area for local residents.
-
D.
Georgengarten
Georgengarten is a large English-style landscape park in Hanover, Germany, known for its expansive lawns, tree-lined avenues, and integration into the historic Herrenhausen Gardens ensemble.
-
E.
Englischer Garten
Englischer Garten is a large public park in Munich, Germany, renowned for its expansive green spaces, beer gardens, and riverside surfing on the Eisbach.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec719c148190a731773ac262221b |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b52845684c8190b6f0676319a6fc3c |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:20 p.m.