Triple
T2179936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha |
E49016
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Marta (Italian) |
E241291
|
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: Marta (Italian) | Statement: [Martha, hasCognate, Marta (Italian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marta (Italian) Context triple: [Martha, hasCognate, Marta (Italian)]
-
A.
Marta (Spanish)
chosen
Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
-
B.
Marta (Polish)
Marta is a common Polish female given name, equivalent to Martha, traditionally associated with Christian and European naming traditions.
-
C.
Paola
Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
-
D.
Stefania
Stefania is a feminine given name of Italian origin, commonly used in Italy and other European countries.
-
E.
Manuela Testolini
Manuela Testolini is a Canadian businesswoman and philanthropist, known for founding the nonprofit In a Perfect World and for her previous marriage to musician Prince.
- 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.