Triple
T2179934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha |
E49016
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Marthe |
E241286
|
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: Marthe | Statement: [Martha, hasCognate, Marthe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marthe Context triple: [Martha, hasCognate, Marthe]
-
A.
Marthe
chosen
Marthe is a feminine given name, commonly used in French and other European languages, that is a variant of the name Martha.
-
B.
Marthe Keller
Marthe Keller is a Swiss actress and former opera director known for her international film career, including prominent roles in 1970s Hollywood thrillers and European cinema.
-
C.
Françoise
Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
-
D.
Marguerite Gaudelet
Marguerite Gaudelet was the wife of French civil engineer Gustave Eiffel, famed designer of the Eiffel Tower.
-
E.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbef0e2f0819080ca457fe3b8b419 |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae653de18481909c3521e060540a38 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:45 p.m.