Triple
T4790123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beata Szydło |
E106580
|
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 Szydło, givenName, Beata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beata Context triple: [Beata Szydło, 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.
Dagmara
Dagmara is a feminine given name, primarily used in Slavic countries, that is a variant of the name Dagmar.
-
C.
Zofia
Zofia is a feminine given name of Slavic origin, particularly common in Poland and other Central and Eastern European countries.
-
D.
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.
-
E.
Sylwia
Sylwia is a feminine given name, primarily used in Poland, that is a cognate of the name Sylvia.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65dce6888190a0b1bdf416fb62b9 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43e8f9dc8190b4e932d179e2f097 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.