Triple
T19697824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cupar railway station |
E473007
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | CUP |
—
|
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: CUP | Statement: [Cupar railway station, stationCode, CUP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CUP Context triple: [Cupar railway station, stationCode, CUP]
-
A.
CUP
The Committee of Union and Progress (CUP) was a dominant early 20th-century Ottoman political organization and ruling party associated with the Young Turk movement and the empire’s final years.
-
B.
CUP
CUP is an academic publishing organization associated with York University, known for producing scholarly books and journals.
-
C.
CUP
chosen
CUP is the National Rail station code for Cupar railway station in Fife, Scotland.
-
D.
CUP
CUP is the abbreviation commonly used for China UnionPay, the Chinese state-backed financial services corporation that operates a major global bank card network.
-
E.
CUP
CUP is the abbreviation for Collectif Ultras Paris, a prominent group of passionate Paris Saint-Germain football supporters known for their organized chants, tifos, and stadium atmosphere.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b2baec81909ee2cd6ead632836 |
completed | April 20, 2026, 3:13 p.m. |
Created at: April 10, 2026, 1:46 p.m.