Triple
T14042684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Kent |
E337883
|
entity |
| Predicate | railwayServiceSeasonality |
P112601
|
FINISHED |
| Object | seasonal stop |
—
|
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: seasonal stop | Statement: [Port Kent, railwayServiceSeasonality, seasonal stop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayServiceSeasonality Context triple: [Port Kent, railwayServiceSeasonality, seasonal stop]
-
A.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
-
B.
railwayLineUsage
Indicates how a railway line is used, such as the type or purpose of traffic or operations it supports.
-
C.
railwayTypeServed
Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
-
D.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
isRailServiceOf
Indicates that a particular rail service operates for, belongs to, or is provided by a specified entity (such as a route, operator, or network).
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de312b94308190bd0961f5bc719c7b |
completed | April 14, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.