Triple
T2115264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beata Ernman |
E43795
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Beata |
E234915
|
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: Beata | Statement: [Beata Ernman, givenName, Beata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beata Context triple: [Beata Ernman, givenName, Beata]
-
A.
Beata
chosen
Beata is a feminine given name of Latin origin, commonly used in various European countries and meaning "blessed" or "happy."
-
B.
Beata Beatrix
Beata Beatrix is a celebrated painting by Dante Gabriel Rossetti that portrays a trance-like Beatrice and exemplifies the spiritual, symbolic style of the Pre-Raphaelite movement.
-
C.
Sylwia
Sylwia is a feminine given name, primarily used in Poland, that is a cognate of the name Sylvia.
-
D.
Magda
Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
-
E.
Klaudija
Klaudija is a feminine given name, commonly used in Slavic countries, that corresponds to the name Claudia.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0724e08190a0a4210d86261d6d |
completed | March 7, 2026, 5:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5194abec8190aab8b7a9ef98da92 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:43 p.m.