Triple
T15419588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K.D. Aubert |
E369337
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Aubert |
E71764
|
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: Aubert | Statement: [K.D. Aubert, familyName, Aubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aubert Context triple: [K.D. Aubert, familyName, Aubert]
-
A.
Aubert
chosen
Aubert is a French given name and surname of Germanic origin, historically associated with medieval nobility and Christian saints.
-
B.
Aubèrt
Aubèrt is a small village in the municipality of Vielha e Mijaran in the Val d'Aran region of Catalonia, Spain.
-
C.
Ambroise
Ambroise is a modern digital revival of classic Didone-style typefaces, characterized by high contrast between thick and thin strokes and elegant, refined letterforms.
-
D.
Aurélien
Aurélien is a French given name commonly used for males, derived from the Latin name Aurelianus.
-
E.
d’Aubigni
d’Aubigni is a variant spelling of the surname d’Aubigny, historically associated with a Norman noble family.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ebce4f48190ba282ecb4fb2f6fa |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7adb848190836fb972bc8744f1 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:20 a.m.