Triple
T14135544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenchurch Street railway station |
E350283
|
entity |
| Predicate | isLondonTerminal |
P99236
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fenchurch Street railway station, isLondonTerminal, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLondonTerminal Context triple: [Fenchurch Street railway station, isLondonTerminal, true]
-
A.
primaryLondonTerminal
Indicates that a given station serves as the main London terminal for a particular rail service or route.
-
B.
secondaryLondonTerminal
Indicates that a location serves as a secondary terminal in London associated with a primary London terminal for a given service or route.
-
C.
isWithinLondonFareSystem
Indicates that an entity (such as a station, stop, or route) is located inside the area covered by the London public transport fare system.
-
D.
originalLondonTerminusLocation
Indicates the location of an entity’s original terminus station in London.
-
E.
isTerminalForSomeTrains
chosen
Indicates that a station or stop serves as the final destination (terminus) for at least one train route.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610e949c8190852d336c9d12bfd0 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:13 a.m.