Triple
T19443285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilmour |
E486405
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Gilmore |
—
|
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: Gilmore | Statement: [Gilmour, hasVariant, Gilmore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilmore Context triple: [Gilmour, hasVariant, Gilmore]
-
A.
Gilmore
chosen
Gilmore is a surname most prominently associated with Artis Gilmore, a Hall of Fame American professional basketball player known for his dominant play in the ABA and NBA.
-
B.
Gilmore
Gilmore is an Australian federal electoral division in New South Wales that includes much of the Shoalhaven region and surrounding coastal areas.
-
C.
Glennon
Glennon is a surname most notably associated with American cinematographer Bert Glennon and various other individuals across sports, literature, and public life.
-
D.
Glenna
Glenna is a feminine given name of Irish origin, often interpreted to mean "valley" or "from the glen."
-
E.
Glenna
Glenna is a fictional character distinguished by her prominent horns, often depicted as a horned or demonic figure in her narrative setting.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63386c520819092bea5d7f259a226 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.