Triple
T11994788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ladies Man |
E285500
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Harry James |
E549257
|
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: Harry James | Statement: [The Ladies Man, castMember, Harry James]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry James Context triple: [The Ladies Man, castMember, Harry James]
-
A.
Harry James
chosen
Harry James was a renowned American jazz trumpeter and bandleader celebrated for his virtuosic playing and popularity during the big band era.
-
B.
Harry Bruce
Harry Bruce was an Australian politician and public figure after whom Queensland’s major Bruce Highway is named.
-
C.
Harry Berkeley James
Harry Berkeley James was a British colonial official in Hong Kong after whom the famous flamingo in the city’s Botanical Gardens was named.
-
D.
Robert James
Robert James is an American businessman best known as the founder of the financial services firm Raymond James Financial.
-
E.
Hal James
Hal James was a theatrical producer best known for his work on the acclaimed Broadway musical "Man of La Mancha."
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47273e1088190b899071baff1375a |
completed | May 1, 2026, 9:29 a.m. |
Created at: April 8, 2026, 9:46 p.m.