Triple
T2056338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Lyon railway |
E45681
|
entity |
| Predicate | lineUsage |
P2529
|
FINISHED |
| Object | mixed traffic |
—
|
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: mixed traffic | Statement: [Paris–Lyon railway, lineUsage, mixed traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineUsage Context triple: [Paris–Lyon railway, lineUsage, mixed traffic]
-
A.
lineUses
Indicates that a particular line (such as a route, service, or connection) makes use of or is implemented using a specified resource, infrastructure, or element.
-
B.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
D.
usesLineCode
Indicates that one entity employs or references a specific line code as part of its operation, identification, or communication.
-
E.
usageInstruction
Indicates that one entity provides guidance or directions on how to properly use, operate, or handle another entity.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9abdb088190991a620e01dc226f |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7ad5a7c8190b92575d6053b3fb7 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:40 p.m.