Triple
T5384697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo station |
E113173
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Reading station |
E43445
|
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: Reading station | Statement: [Waterloo station, connectsTo, Reading station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reading station Context triple: [Waterloo station, connectsTo, Reading station]
-
A.
Reading railway station
chosen
Reading railway station is a major railway hub in Berkshire, England, serving as a key interchange on the Great Western Main Line and other routes.
-
B.
The Station
The Station is a painting by British artist L. S. Lowry, known for its distinctive depiction of industrial urban life with stylized figures and stark architectural forms.
-
C.
Central Station
Central Station is a key light rail stop on the METRO Green Line serving as an important transit hub in its area.
-
D.
Central Station
Central Station is a 1998 Brazilian drama film by Walter Salles that follows the emotional journey of a retired schoolteacher and a young boy traveling across Brazil in search of his father.
-
E.
Central Station
Central Station is a key elevated stop on Jacksonville’s automated Skyway people mover system in downtown Jacksonville, Florida.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86f5a7388190aa4ba2052afca74e |
completed | March 20, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf295030b081909bea5e946aac098b |
completed | March 21, 2026, 11:27 p.m. |
Created at: March 20, 2026, 2:03 p.m.