Triple
T7356785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burton "Gus" Guster |
E169645
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Burton |
E428850
|
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: Burton | Statement: [Burton "Gus" Guster, givenName, Burton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burton Context triple: [Burton "Gus" Guster, givenName, Burton]
-
A.
Burton
Burton is the surname of acclaimed American filmmaker Tim Burton, known for his dark, gothic, and whimsical visual style.
-
B.
Burton
chosen
Burton is a masculine given name of English origin, notably borne by the American actor Burt Lancaster.
-
C.
Shadbolt
Shadbolt is a surname most notably associated with Sir Nigel Shadbolt, a prominent British computer scientist and artificial intelligence researcher.
-
D.
Bortus
Bortus is a stoic, duty-bound Moclan officer serving as second-in-command aboard the exploratory spaceship in the sci-fi comedy series "The Orville."
-
E.
Buriton
Buriton is a rural village and civil parish in Hampshire, England, known for its scenic setting near the South Downs and its historic church and ponds.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f13a62e48190a2d1781a630aa9f0 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7faa6a5d88190b969b7783edc67b7 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:06 p.m.