Triple
T21438136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King John |
E528866
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Hubert |
—
|
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: Hubert | Statement: [King John, featuresCharacter, Hubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hubert Context triple: [King John, featuresCharacter, Hubert]
-
A.
Hubert
chosen
Hubert is a masculine given name of Germanic origin meaning "bright heart" or "shining intellect," historically borne by saints, nobles, and notable public figures.
-
B.
Roger Hubert
Roger Hubert was a French cinematographer known for his work on mid-20th-century films, contributing to the visual style of classic French cinema.
-
C.
Huberte Rupert
Huberte Rupert is a member of South Africa’s prominent Rupert family, known for its extensive business and philanthropic influence.
-
D.
Thomas Hubert
Thomas Hubert is an author known for his work on the artificial intelligence program AlphaGo Zero.
-
E.
Hugon
Hugon is a French surname borne by various individuals, including figures in the arts, politics, and academia.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b53972e48190bc8bbc543173854c |
completed | April 22, 2026, 11:47 a.m. |
Created at: April 16, 2026, 6:04 p.m.