Triple
T5846302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen I of Hungary |
E129719
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Sarolt |
E129719
|
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: Sarolt | Statement: [Stephen I of Hungary, mother, Sarolt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarolt Context triple: [Stephen I of Hungary, mother, Sarolt]
-
A.
Sarolt
chosen
Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
-
B.
Somlyó
Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
-
C.
Sándor
Sándor is a Hungarian given name, traditionally used as the local form of Alexander.
-
D.
Harkányi
Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
-
E.
Hadár
Hadár is the guiding motto of the Betar youth movement, emphasizing Jewish pride, dignity, and disciplined self-respect.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0351157508190a78d2a7141e0cee8 |
completed | March 22, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b0fb0f68819091018926ee4c7bb8 |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:55 p.m.