Triple
T9730440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Ellis |
E235724
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | George |
unclear NED1
|
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: George | Statement: [George Ellis, givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [George Ellis, givenName, George]
-
A.
George
George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
-
B.
George
George is the given name of the Hero of Manila Bay, most famously associated with U.S. Admiral George Dewey, who led the decisive naval victory at the Battle of Manila Bay during the Spanish–American War.
-
C.
George
George is the given name of George Goring, Lord Goring, a prominent Royalist commander during the English Civil War.
-
D.
George
George is the given first name of G. Gordon Liddy, the former FBI agent and key operative in the Watergate scandal.
-
E.
George
George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb0ff488190ac32ed304a3cd3bc |
completed | April 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcc45bfc81909b86d10598d9bd39 |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:21 p.m.