Triple
T38188785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Manchester |
E1005393
|
entity |
| Predicate | hasHighSpeedRailStatusToManchester |
P200985
|
FINISHED |
| Object | partly cancelled |
—
|
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: partly cancelled | Statement: [London–Manchester, hasHighSpeedRailStatusToManchester, partly cancelled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSpeedRailStatusToManchester Context triple: [London–Manchester, hasHighSpeedRailStatusToManchester, partly cancelled]
-
A.
hasRailTerminusInManchester
Indicates that something has its rail terminus (end point of a railway line or service) located in Manchester.
-
B.
hasHighSpeedLine
Indicates that there exists a high-speed rail line connection between the related entities.
-
C.
hasNationalRailService
Indicates that a place or facility is served by a country's national rail transportation network.
-
D.
hasHighSpeedRailStation
Indicates that a location is served by a high-speed rail station where high-speed trains regularly stop.
-
E.
hasNationalRailCategory
Indicates that an entity is assigned a specific classification or category within a national rail system.
- F. None of above. chosen
Provenance (4 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
| PDg | Predicate description generation | batch_69ffbf8402c48190a9bf3c3fcb874508 |
completed | May 9, 2026, 11:13 p.m. |
Created at: May 3, 2026, 4:29 p.m.