Triple
T10180883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laetitia |
E236777
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Lætitia |
E236777
|
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: Lætitia | Statement: [Laetitia, hasVariant, Lætitia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lætitia Context triple: [Laetitia, hasVariant, Lætitia]
-
A.
Fleurie
Fleurie is a renowned Beaujolais cru appellation in eastern France, celebrated for its elegant, floral Gamay-based red wines.
-
B.
Laetitia
chosen
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
C.
Sevdaliza
Sevdaliza is an Iranian-Dutch singer, songwriter, and producer known for her experimental blend of electronic, trip-hop, and avant-pop music paired with highly conceptual visual art.
-
D.
Cécile
Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
-
E.
Melody Gardot
Melody Gardot is an American jazz singer-songwriter known for her sultry vocals, sophisticated arrangements, and blend of jazz, blues, and bossa nova influences.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded315f14819085727bd9b4363d10 |
completed | April 2, 2026, 4:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d301373a008190b8d39a8db4167e4f |
completed | April 6, 2026, 12:41 a.m. |
Created at: March 30, 2026, 9:11 p.m.