Triple
T3984165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homer Murray |
E86829
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Luke Murray |
E162186
|
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: Luke Murray | Statement: [Homer Murray, relative, Luke Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luke Murray Context triple: [Homer Murray, relative, Luke Murray]
-
A.
Luke Murray
chosen
Luke Murray is an American basketball coach known for his assistant coaching roles at several major college programs and as the son of actor Bill Murray.
-
B.
Tim Murray
Tim Murray is a collegiate sports administrator best known for serving as the athletic director of the Marist Red Foxes.
-
C.
Murray Bartlett
Murray Bartlett is an Australian actor best known for his acclaimed performances in television series such as "Looking," "The White Lotus," and "The Last of Us."
-
D.
Don Murray
Don Murray is an American actor best known for his Oscar-nominated film debut in the 1956 drama "Bus Stop" opposite Marilyn Monroe.
-
E.
John Dawson
John Dawson is a fictional character named John Dawson who appears in the work featuring the character Dawn.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9de58d48190969f354a1bf0df94 |
completed | March 9, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5768c29f08190baa35f395ebee6bb |
completed | March 14, 2026, 2:54 p.m. |
Created at: March 9, 2026, 3:33 p.m.