Triple
T830976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audie Murphy |
E17964
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Murphy |
E67931
|
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: Murphy | Statement: [Audie Murphy, familyName, Murphy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murphy Context triple: [Audie Murphy, familyName, Murphy]
-
A.
Murphy
chosen
Murphy is a common Irish-origin surname borne by numerous notable individuals across entertainment, politics, sports, and other fields.
-
B.
Mervin
Mervin is a masculine given name of English origin, often used as a variant of Marvin or Mervyn.
-
C.
Melvin
Melvin is the full given name of legendary American voice actor and comedian Mel Blanc, famed for voicing many iconic Looney Tunes characters.
-
D.
Harvey
Harvey is a botanist and taxonomist known for formally describing the plant genus Romneya.
-
E.
Curtis
Curtis is a common English surname of Norman origin, historically meaning "courteous" or "polite."
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb4be948190ae757df85bdc40e4 |
completed | March 1, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7929458648190a88390a1a3207ad0 |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.