Triple
T16619284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jodie Holmes |
E403779
|
entity |
| Predicate | hasLastName |
P18
|
FINISHED |
| Object | Holmes |
E5614
|
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: Holmes | Statement: [Jodie Holmes, hasLastName, Holmes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holmes Context triple: [Jodie Holmes, hasLastName, Holmes]
-
A.
Holmes
chosen
Holmes is a common English surname borne by numerous notable figures, including writers, jurists, and fictional characters such as Sherlock Holmes.
-
B.
Holmes
Holmes is a consumer brand best known for its home comfort products such as fans, heaters, and air purifiers.
-
C.
Hugh Sherlock
Hugh Sherlock was a Jamaican clergyman, social worker, and poet best known for writing the lyrics of Jamaica’s national anthem.
-
D.
Jerry Sherlock
Jerry Sherlock was a film producer best known for producing the 1990 submarine thriller "The Hunt for Red October."
-
E.
Holmes & Watson
Holmes & Watson is a 2018 slapstick comedy film that parodies Arthur Conan Doyle’s Sherlock Holmes stories, starring Will Ferrell and John C. Reilly as the iconic detective duo.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754c934c8190a0a8ddd747681aa7 |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007db0b4348190beb573bc3df98125 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.