Triple
T16972459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin-Westkreuz station |
E411719
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | S7 |
E139349
|
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: S7 | Statement: [Berlin-Westkreuz station, servedByLine, S7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S7 Context triple: [Berlin-Westkreuz station, servedByLine, S7]
-
A.
S7
S7 is a line of the Rhine-Main S-Bahn rapid transit network serving the Frankfurt Rhine-Main metropolitan region in Germany.
-
B.
S7
chosen
S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
-
C.
S7
S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
-
D.
S75
S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
-
E.
S7 Technics
S7 Technics is a Russian aircraft maintenance, repair, and overhaul (MRO) company that services both S7 Airlines and other carriers.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ae47f08190a13e98d20aba7f16 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d471d4248190acf40b6c11926a65 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.