Triple
T19999694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honey |
E494283
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | George |
—
|
NE NERFINISHED |
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: [Honey, associatedWithCharacter, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Honey, associatedWithCharacter, George]
-
A.
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.
-
B.
George
George is the given name of George Goring, Lord Goring, a prominent Royalist commander during the English Civil War.
-
C.
George
chosen
George is the given name of Lord Goring, a witty and fashionable character in Oscar Wilde’s play "An Ideal Husband."
-
D.
George
George is the given name of George Grosz, a prominent German artist known for his biting caricatures and critical depictions of Weimar-era society.
-
E.
George
George is the given name of George Hastings, 1st Earl of Huntingdon of the second creation, an English nobleman of the Tudor period.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a09bdc819083305b08a11c6e34 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:32 p.m.