Triple
T20088496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Harrow Underground station |
E496201
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object | WHR |
—
|
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: WHR | Statement: [West Harrow Underground station, stationCode, WHR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WHR Context triple: [West Harrow Underground station, stationCode, WHR]
-
A.
WHR
chosen
WHR is the commonly used abbreviation for the World Health Report, the World Health Organization’s flagship publication on global health statistics, trends, and policy.
-
B.
WRH
WRH is the National Rail station code for Worthing railway station in West Sussex, England.
-
C.
WHE
WHE is the National Rail station code for Whalley railway station in Lancashire, England.
-
D.
WEH
WEH is the IATA airport code for Weihai Dashuibo Airport, a commercial airport serving the city of Weihai in Shandong Province, China.
-
E.
BWh
BWh is the Köppen climate classification code for hot desert climates characterized by extremely low rainfall and high temperatures.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655d65a88190a510132f36341b6c |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 11:17 p.m.