Triple
T1834676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Werburgh's Road tram stop |
E41037
|
entity |
| Predicate | airportLineRole |
P33934
|
FINISHED |
| Object | intermediate stop on Airport Line |
—
|
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: intermediate stop on Airport Line | Statement: [St Werburgh's Road tram stop, airportLineRole, intermediate stop on Airport Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportLineRole Context triple: [St Werburgh's Road tram stop, airportLineRole, intermediate stop on Airport Line]
-
A.
airportRole
Indicates that an entity serves a specific functional role or capacity within the context of an airport.
-
B.
belongsToAirport
Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
-
C.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
D.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
E.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.