Triple
T11448720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Napier |
E271335
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Charles Napier |
E271335
|
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: Charles Napier | Statement: [Charles Napier, name, Charles Napier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Napier Context triple: [Charles Napier, name, Charles Napier]
-
A.
Charles Napier
chosen
Charles Napier was a prominent 19th-century British naval officer and admiral known for his service in the Royal Navy during the Napoleonic Wars and later conflicts.
-
B.
Charles Napier
Charles Napier was an American character actor known for his rugged, authoritative roles in action films and television, often portraying military or law-enforcement figures.
-
C.
Colin Gibson
Colin Gibson is an Australian production designer best known for his Oscar-winning work on the visually striking post-apocalyptic film Mad Max: Fury Road.
-
D.
Peter Riddell
Peter Riddell is a British political journalist and commentator who has held senior roles in public policy analysis, including leading the Institute for Government.
-
E.
Campbell Dixon
Campbell Dixon was a British screenwriter active in the early 20th century, known for adapting literary works for the screen.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c6e496c8190b0a1919c29d4ee60 |
completed | April 9, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d3cb63408190a96b97f716d46082 |
completed | April 20, 2026, 7:20 a.m. |
Created at: April 8, 2026, 9:35 p.m.