Triple
T18493145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo to Southampton main line |
E451867
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Reading Line |
—
|
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: Reading Line | Statement: [Waterloo to Southampton main line, connectsTo, Reading Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reading Line Context triple: [Waterloo to Southampton main line, connectsTo, Reading Line]
-
A.
Reading Line
chosen
Reading Line is a British railway line associated with services operated by the train company WAT.
-
B.
Line by Line
Line by Line is a jazz album by acclaimed bassist John Patitucci, showcasing his virtuosic playing and sophisticated compositions.
-
C.
Line
"Line" is a one-act absurdist stage play by Israel Horovitz that explores power struggles and manipulation among five characters waiting in an undefined queue.
-
D.
Loop Line
Loop Line is a circular rapid transit route within the Chongqing Metro system that connects multiple key districts in Chongqing, China.
-
E.
Read Between the Lines
Read Between the Lines is a song featured on the album "One to One."
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532be5e988190aae93a66f6e5f857 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:35 a.m.