Triple
T24989828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-10 |
E625414
|
entity |
| Predicate | sharesStationWithOtherLines |
P61736
|
FINISHED |
| Object | Yes (Ginza Line, Asakusa Line at Nihonbashi) |
—
|
LITERAL 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: Yes (Ginza Line, Asakusa Line at Nihonbashi) | Statement: [T-10, sharesStationWithOtherLines, Yes (Ginza Line, Asakusa Line at Nihonbashi)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesStationWithOtherLines Context triple: [T-10, sharesStationWithOtherLines, Yes (Ginza Line, Asakusa Line at Nihonbashi)]
-
A.
sharesStationsWith
chosen
Indicates that two transit routes or lines have one or more stations or stops in common along their paths.
-
B.
sharesTrunkLineWith
Indicates that two entities are connected to or use the same primary communication or utility trunk line.
-
C.
sharesLineUpWith
Indicates that two entities participate together in the same lineup or roster at the same time.
-
D.
stationSharing
Indicates a relationship where multiple services, lines, or operators use or serve the same station location.
-
E.
sharesTracksWith
Indicates that two entities have one or more tracks in common, such as shared audio, rail, or route segments.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 18, 2026, 6:03 a.m.