Triple
T10446302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurentius |
E246296
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Laurent |
E694397
|
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: Laurent | Statement: [Laurentius, hasVariant, Laurent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurent Context triple: [Laurentius, hasVariant, Laurent]
-
A.
Laurent
Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
-
B.
Laurent
Laurent is a central figure in Émile Zola’s novel "Thérèse Raquin," known as Thérèse’s lover and accomplice in a dark, psychologically driven crime.
-
C.
Laurent
Laurent is a nomadic vampire in the Twilight series who initially allies with James and Victoria before later attempting to betray the Cullens.
-
D.
Laurent
Laurent is a French surname historically associated with various notable figures and families.
-
E.
Laurent
chosen
Laurent is a French given name, commonly used as the French form of Lawrence.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdc0520c819098d2d53ee46a89ae |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d933a2daf481908300a12d0f794e4c |
completed | April 10, 2026, 5:30 p.m. |
Created at: April 6, 2026, 12:16 p.m.