Triple
T20049353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunbar railway station |
E499150
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | DUN |
—
|
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: DUN | Statement: [Dunbar railway station, stationCode, DUN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DUN Context triple: [Dunbar railway station, stationCode, DUN]
-
A.
DUN
chosen
DUN is the standard abbreviation used to represent the professional ice hockey team Dundee Stars.
-
B.
DUS
DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
-
C.
Dxun
Dxun is a dangerous, jungle-covered moon of Onderon in the Star Wars universe, known for its ferocious wildlife, Mandalorian war history, and significance during the Old Republic era.
-
D.
Dus
"Dus" is a 2005 Indian action thriller film known for its ensemble cast, high-octane stunts, and a plot centered on an anti-terrorism mission.
-
E.
Doud
Doud is the maiden surname of Mamie Eisenhower, the First Lady of the United States during Dwight D. Eisenhower’s presidency.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:37 p.m.