Triple
T556808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main North railway line |
E11958
|
entity |
| Predicate | usedByService |
P1294
|
FINISHED |
| Object | intercity passenger trains |
—
|
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: intercity passenger trains | Statement: [Main North railway line, usedByService, intercity passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByService Context triple: [Main North railway line, usedByService, intercity passenger trains]
-
A.
servedByService
chosen
Indicates that something is provided, handled, or fulfilled by a particular service.
-
B.
usedBySystem
Indicates that something is utilized or operated by a particular system.
-
C.
usedByTool
Indicates that a particular tool is employed or operated by a specified agent or entity.
-
D.
usedByPerson
Indicates that something (such as an object, tool, or resource) is utilized or employed by a person.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.