Triple
T2203748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Rose |
E50549
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Murray |
E33747
|
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: Murray | Statement: [Murray Rose, givenName, Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murray Context triple: [Murray Rose, givenName, Murray]
-
A.
Murray
Murray is a suburban city in the Salt Lake Valley of Utah, known for its central location in the metropolitan area and its mix of residential, commercial, and medical facilities.
-
B.
Murray
chosen
Murray is a masculine given name of Scottish origin that has been borne by various notable figures, including physicist Murray Gell-Mann.
-
C.
Murray
Murray is an electoral district in the New South Wales Legislative Assembly, covering a large rural region in the state's southwest.
-
D.
Murray Louis
Murray Louis was an influential American modern dancer and choreographer, best known for his work with the Alwin Nikolais Dance Company and for his innovative, theatrical approach to movement.
-
E.
Tom Murray
Tom Murray was an American character actor of the silent film era, known for his supporting roles in early Hollywood productions.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa481308190bda187c03162e0b6 |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae65473fd48190b58dba4205776096 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.