Triple
T1354335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finley |
E28951
|
entity |
| Predicate | electoralDistrictState |
P19338
|
FINISHED |
| Object | Murray |
E119974
|
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: [Finley, electoralDistrictState, Murray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murray Context triple: [Finley, electoralDistrictState, Murray]
-
A.
Murray
Murray is a masculine given name of Scottish origin that has been borne by various notable figures, including physicist Murray Gell-Mann.
-
B.
Murray
chosen
Murray is an electoral district in the New South Wales Legislative Assembly, covering a large rural region in the state's southwest.
-
C.
Tom Murray
Tom Murray was an American character actor of the silent film era, known for his supporting roles in early Hollywood productions.
-
D.
Murray Sueter
Murray Sueter was a pioneering British naval officer and aviation advocate who played a key role in the early development of naval air power in the United Kingdom.
-
E.
Will Poole
Will Poole is an American technology executive and impact investor known for his leadership roles at Microsoft and his work in social entrepreneurship and inclusive innovation.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26e916c8190b4b324df87f4c121 |
completed | March 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acce6bf6188190a0e1c8acd16b8088 |
completed | March 8, 2026, 1:18 a.m. |
Created at: March 1, 2026, 7:56 p.m.