Triple
T23532149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmut Jahn |
E576598
|
entity |
| Predicate | designed |
P184
|
FINISHED |
| Object | Messeturm |
—
|
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: Messeturm | Statement: [Helmut Jahn, designed, Messeturm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Messeturm Context triple: [Helmut Jahn, designed, Messeturm]
-
A.
Messeturm
chosen
Messeturm is a prominent postmodern skyscraper in Frankfurt, Germany, known as one of the city's tallest and most recognizable landmarks.
-
B.
Blaserturm
Blaserturm is a historic medieval watch and bell tower that serves as one of the most recognizable symbols of the German city of Ravensburg.
-
C.
Schmalzturm
Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
-
D.
Schmalzturm
Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
-
E.
Wachtturm
Wachtturm is one of the historic defensive towers incorporated into Lucerne’s medieval Musegg Wall fortifications in Switzerland.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac78581c8190bd9d09ce2be8029d |
completed | April 29, 2026, 7 a.m. |
Created at: April 17, 2026, 6:09 p.m.