Triple
T16675725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hong Kong Garden |
E405210
|
entity |
| Predicate | hasGuitarist |
P15278
|
FINISHED |
| Object | John McKay |
E405193
|
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: John McKay | Statement: [Hong Kong Garden, hasGuitarist, John McKay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John McKay Context triple: [Hong Kong Garden, hasGuitarist, John McKay]
-
A.
John McKay
chosen
John McKay is a British guitarist best known for his influential early work with the post-punk band Siouxsie and the Banshees, where his innovative playing helped define their sound.
-
B.
John McKay
John McKay is a screenwriter and director known for his work on the film "Hong Kong Garden."
-
C.
John McKinley
John McKinley was an Associate Justice of the U.S. Supreme Court in the mid-19th century, known for his participation in significant cases involving federal power and economic development.
-
D.
Tom Truscott
Tom Truscott is an American computer scientist best known as a co-creator of Usenet, one of the earliest and most influential distributed discussion systems on the internet.
-
E.
Terry McCaleb
Terry McCaleb is a retired FBI profiler and heart transplant recipient who becomes an unlikely investigator in Michael Connelly’s crime novel "Blood Work."
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6b69cc8190b19632e1b4293569 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a51169b881909216ab1055752978 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:19 a.m.