Triple
T31372124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willy-Brandt-Platz (Frankfurt am Main) |
E800190
|
entity |
| Predicate | hasNearbyTramLine |
P172293
|
FINISHED |
| Object | Frankfurt tram line 11 |
—
|
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 tram line 11 | Statement: [Willy-Brandt-Platz (Frankfurt am Main), hasNearbyTramLine, Frankfurt tram line 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyTramLine Context triple: [Willy-Brandt-Platz (Frankfurt am Main), hasNearbyTramLine, Frankfurt tram line 11]
-
A.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
B.
nearTramwayLine
chosen
Indicates that one entity is located close to a tramway line in physical space.
-
C.
hasNearbyLine
Indicates that one entity is located close to, or in the vicinity of, a particular line or linear feature.
-
D.
hasNearbyOvergroundLine
Indicates that one entity is located close to an above-ground railway or transit line associated with the other entity.
-
E.
hasTramTrainLine
Indicates that there exists a tram-train line connection or service linking the related entities.
- 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_69feecf1bb248190ba30f0bb1d22ee08 |
completed | May 9, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69feea5f27748190b223ee4e3ba5a678 |
completed | May 9, 2026, 8:03 a.m. |
Created at: April 29, 2026, 9:18 p.m.