Triple
T23259764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British sector |
E581970
|
entity |
| Predicate | includedBorough |
P54716
|
FINISHED |
| Object | Tiergarten |
—
|
NE NERFINISHED |
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: [British sector, includedBorough, Tiergarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiergarten Context triple: [British sector, includedBorough, Tiergarten]
-
A.
Tiergarten
chosen
Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
-
B.
Tiergarten park
Tiergarten park is a historic public park in the German town of Kleve, known for its landscaped grounds, walking paths, and recreational green spaces.
-
C.
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.
-
D.
Volksgarten
Volksgarten is a historic public park in central Vienna renowned for its formal rose gardens, neoclassical monuments, and location along the Ringstrasse.
-
E.
Großer Tiergarten park
Großer Tiergarten park is a large, historic urban park in central Berlin known for its wooded landscapes, lakes, and cultural landmarks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c7ec148190b01fd215a0c1daa1 |
completed | April 29, 2026, 5:19 a.m. |
Created at: April 17, 2026, 4:11 p.m.