Triple
T31371763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankfurt S-Bahn line S3 |
E800180
|
entity |
| Predicate | usesTunnelSection |
P155518
|
FINISHED |
| Object | Frankfurt City Tunnel |
—
|
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: Frankfurt City Tunnel | Statement: [Frankfurt S-Bahn line S3, usesTunnelSection, Frankfurt City Tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTunnelSection Context triple: [Frankfurt S-Bahn line S3, usesTunnelSection, Frankfurt City Tunnel]
-
A.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
B.
hasTunnelSections
Indicates that an entity includes or is composed of multiple distinct tunnel segments or portions.
-
C.
tunnelUse
chosen
Indicates that one entity makes use of or passes through a tunnel associated with another entity.
-
D.
hasTunnel
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
E.
operatorOfTunnelSection
Indicates that an entity is responsible for operating or managing a specific section of a tunnel.
- F. None of above.
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_69f224e6b7448190ac6bf97ad7364160 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 29, 2026, 9:18 p.m.