Triple
T22922400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlisle railway station |
E568896
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | CAR |
—
|
NE NERFINISHED |
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: CAR | Statement: [Carlisle railway station, hasAbbreviation, CAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAR Context triple: [Carlisle railway station, hasAbbreviation, CAR]
-
A.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
B.
CAR
CAR is the commonly used abbreviation for the Chief of Army Reserve, the senior leader responsible for commanding and overseeing the United States Army Reserve.
-
C.
CAR
chosen
CAR is the National Rail station code for Carlisle railway station in Cumbria, England.
-
D.
CAR
CAR is the commonly used abbreviation for Rugby Africa, the governing body for rugby union on the African continent.
-
E.
CAR
CAR is the station code assigned to Carson station, identifying it within the rail network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d6841c81908df6d4e501860a15 |
completed | April 29, 2026, 3:53 a.m. |
Created at: April 17, 2026, 3:43 p.m.