Triple
T17404088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barfüsserplatz |
E423167
|
entity |
| Predicate | hasNearbyStreet |
P8235
|
FINISHED |
| Object | Freie Strasse |
—
|
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: Freie Strasse | Statement: [Barfüsserplatz, hasNearbyStreet, Freie Strasse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freie Strasse Context triple: [Barfüsserplatz, hasNearbyStreet, Freie Strasse]
-
A.
Freie Strasse
chosen
Freie Strasse is one of Basel’s main historic shopping streets, known for its upscale boutiques and central location in the Old Town.
-
B.
Kramerstraße
Kramerstraße is a historic street in Hanover’s Old Town known for its preserved half-timbered houses, traditional shops, and medieval charm.
-
C.
Luxemburger Straße
Luxemburger Straße is a street located near Leopoldplatz in Berlin, Germany.
-
D.
Schweizer Straße
Schweizer Straße is a prominent street in Frankfurt am Main, Germany, known for its shops, cafes, and role as a key thoroughfare in the Sachsenhausen district.
-
E.
Berger Straße
Berger Straße is a prominent and lively shopping and dining street in Frankfurt am Main, known for its mix of boutiques, cafés, bars, and traditional Hessian pubs.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b068248819088871d79f8a38f30 |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.