Triple
T2730216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District line |
E60293
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Wimbledon |
E61345
|
NE 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: Wimbledon | Statement: [District line, terminus, Wimbledon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wimbledon Context triple: [District line, terminus, Wimbledon]
-
A.
Wimbledon
chosen
Wimbledon is a district in southwest London best known for hosting the prestigious annual Wimbledon tennis championships, the oldest tennis tournament in the world.
-
B.
National Tennis Centre
The National Tennis Centre is a premier tennis training and competition facility located at the University of Stirling in Scotland.
-
C.
Australian Open
The Australian Open is one of tennis's four Grand Slam tournaments, held annually in Melbourne and known for its hard courts and intense summer conditions.
-
D.
French Open
The French Open is one of tennis's four major Grand Slam tournaments, renowned for its clay courts and held annually at Roland Garros in Paris.
-
E.
US Open (tennis)
The US Open (tennis) is one of the four Grand Slam tournaments, a major annual hard-court championship that attracts the world’s top professional players.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaeca6208190a586afb00747146a |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb69c9f648190bbbcfa42ab68c6f2 |
completed | March 10, 2026, 6:13 a.m. |
Created at: March 6, 2026, 9:56 p.m.