Triple
T4601542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margherita |
E100329
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Margherite |
E110139
|
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: Margherite | Statement: [Margherita, hasVariantForm, Margherite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margherite Context triple: [Margherita, hasVariantForm, Margherite]
-
A.
Margueritte
Margueritte is a given name and surname, most commonly recognized as a French variant or spelling related to the name Marguerite.
-
B.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
-
C.
Marguerite
chosen
Marguerite is a French given name, equivalent to Margaret, commonly used for women and also meaning "daisy" in French.
-
D.
Isabelle
Isabelle is a popular character from the Animal Crossing series who also appears as a playable racer in Mario Kart 8.
-
E.
Marthe
Marthe is a feminine given name, commonly used in French and other European languages, that is a variant of the name Martha.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd597346a08190b47eda3b73076f8b |
completed | March 20, 2026, 2:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfa60b3348190ac8e28f9e78e1d99 |
completed | March 21, 2026, 1:54 a.m. |
Created at: March 20, 2026, 1:11 p.m.