Triple
T21513243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U4 |
E530779
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | Innsbrucker Platz |
—
|
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: Innsbrucker Platz | Statement: [U4, hasTerminus, Innsbrucker Platz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Innsbrucker Platz Context triple: [U4, hasTerminus, Innsbrucker Platz]
-
A.
Innsbrucker Platz
chosen
Innsbrucker Platz is a public square in Berlin, Germany, known as a local traffic and transport hub in the Schöneberg district.
-
B.
Klosters Platz
Klosters Platz is a central village and transport hub in the Swiss Alps that serves as a primary gateway to the surrounding ski resorts and mountain activities.
-
C.
Kagraner Platz
Kagraner Platz is a public square and major transport hub in Vienna’s 22nd district, Donaustadt.
-
D.
Karolinenplatz
Karolinenplatz is a prominent square in central Munich, Germany, known for its circular layout and the Obelisk monument commemorating Bavarian soldiers who died in Napoleon’s Russian campaign.
-
E.
Rosenheimer Platz
Rosenheimer Platz is a central square and transport hub in Munich’s Haidhausen district, known for its busy S-Bahn station and surrounding shops and cafes.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea88e6fc8190a4b73b8d32dae5a8 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.