Triple
T19314925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landericus |
E483069
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Landry |
—
|
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: Landry | Statement: [Landericus, hasShortForm, Landry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landry Context triple: [Landericus, hasShortForm, Landry]
-
A.
Landry
Landry is a surname most famously associated with Tom Landry, the legendary longtime head coach of the Dallas Cowboys in the National Football League.
-
B.
Broussard
Broussard is a central character in the science fiction television series "Colony," known for his role in the human resistance against an alien occupation.
-
C.
Landri
chosen
Landri is a given name, historically used as a variant of the medieval name Landericus.
-
D.
LaMarche
LaMarche is the surname of Maurice LaMarche, a Canadian-American voice actor best known for his work on animated series such as "Pinky and the Brain" and "Futurama."
-
E.
Taillibert
Taillibert is a French surname most notably associated with architect Roger Taillibert, known for designing major sports complexes such as Montreal's Olympic Stadium.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d833034819092a8414d5e0fc26e |
completed | April 20, 2026, 11:26 a.m. |
Created at: April 10, 2026, 1:32 p.m.