Triple
T6335834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S41 |
E142487
|
entity |
| Predicate | stopsAt |
P6657
|
FINISHED |
| Object | Halensee station |
E576466
|
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: Halensee station | Statement: [S41, stopsAt, Halensee station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halensee station Context triple: [S41, stopsAt, Halensee station]
-
A.
Halensee station
chosen
Halensee station is a Berlin S-Bahn railway station in the Charlottenburg-Wilmersdorf district, serving as a local transit stop on the city’s western ring line.
-
B.
Jungfernheide station
Jungfernheide station is a major public transport hub in Berlin’s Charlottenburg-Nord district, serving S-Bahn, U-Bahn, and regional rail lines.
-
C.
Ostkreuz station
Ostkreuz station is a major railway and S-Bahn interchange in Berlin, Germany, serving as one of the city's busiest public transport hubs.
-
D.
Berlin-Schöneberg station
Berlin-Schöneberg station is a railway station in Berlin’s Schöneberg district, serving as a local transport hub for S-Bahn and regional rail services.
-
E.
Berlin-Wannsee station
Berlin-Wannsee station is a major railway and S-Bahn hub in southwestern Berlin, serving as an important interchange for regional, suburban, and long-distance trains near the Wannsee lake.
- 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654a88a881908d5cb2aa7f22c4c7 |
completed | March 22, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c669d97d348190bca19013edbf436c |
completed | March 27, 2026, 11:28 a.m. |
Created at: March 22, 2026, 4:30 p.m.