Triple
T16387765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U4 line |
E397966
|
entity |
| Predicate | hasInterchangeWithLine |
P73851
|
FINISHED |
| Object | U2 line |
E297622
|
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: U2 line | Statement: [U4 line, hasInterchangeWithLine, U2 line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: U2 line Context triple: [U4 line, hasInterchangeWithLine, U2 line]
-
A.
U2 line
chosen
The U2 line is a rapid transit route of the Frankfurt U-Bahn network that connects central Frankfurt with several outlying districts.
-
B.
U Line
U Line is a light metro line in the Seoul metropolitan area that serves the city of Uijeongbu with driverless trains on an elevated and mostly automated system.
-
C.
U1 line
The U1 line is a route of the Frankfurt U-Bahn rapid transit system that connects central Frankfurt with several northern suburbs.
-
D.
U9 line
The U9 line is a major Berlin U-Bahn subway route running north–south through the city and serving districts such as Wilmersdorf.
-
E.
U3 line
The U3 line is a route of the Frankfurt U-Bahn rapid transit system that connects central Frankfurt with its northwestern suburbs.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263e1534819081a6bf5006c611c5 |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356ed47c819085aaf101459dd55c |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.