Triple
T20434223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S1 (Stuttgart S-Bahn) |
E501208
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | S1 |
—
|
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: S1 | Statement: [S1 (Stuttgart S-Bahn), hasAbbreviation, S1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S1 Context triple: [S1 (Stuttgart S-Bahn), hasAbbreviation, S1]
-
A.
S1
S1 is one of Munich’s S-Bahn commuter rail lines that connects the city center with its northwestern suburbs and Munich Airport.
-
B.
S1
S1 is the professional alias of Symbolyc One, a Grammy-winning American hip-hop and R&B record producer known for his work with artists like Kanye West and Beyoncé.
-
C.
S1
S1 is a key commuter rail line of the Berlin S-Bahn network, connecting central Berlin with its northern and southwestern suburbs.
-
D.
S1
S1 is a commuter rail line of the Nuremberg S-Bahn network serving the greater Nuremberg metropolitan area in Germany.
-
E.
S1
chosen
S1 is a key commuter rail line of the Stuttgart S-Bahn network, connecting central Stuttgart with its surrounding suburbs and regional destinations.
- 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_69e0b4ab3cfc8190ac9bf32e932316b1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e685ecf7ac81908e9c2ef4348fb281 |
completed | April 20, 2026, 8 p.m. |
Created at: April 16, 2026, 11:31 a.m.