Triple
T9403263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Procopius |
E226525
|
entity |
| Predicate | wroteAbout |
P2831
|
FINISHED |
| Object | Antonina |
E555792
|
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: Antonina | Statement: [Procopius, wroteAbout, Antonina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antonina Context triple: [Procopius, wroteAbout, Antonina]
-
A.
Antonina
chosen
Antonina was a prominent Byzantine noblewoman and influential wife of the famed general Belisarius, noted for her political acumen and close association with Empress Theodora in the 6th century.
-
B.
Antonina
Antonina is one of the three central women whose intertwined personal and professional lives are followed over several decades in the Soviet drama film "Moscow Does Not Believe in Tears."
-
C.
Antónia
Antónia is a feminine given name commonly used in various European languages, often as a variant of Antonia.
-
D.
Rositsa
Rositsa is a river in northern Bulgaria that serves as a significant tributary of the Yantra River.
-
E.
Praskovya
Praskovya is the given name of Pasha Angelina, a renowned Soviet female tractor driver and labor heroine.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd51bf7e5c8190850b671778496150 |
completed | April 1, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1012ca6c0819098c427233d226dd2 |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:46 p.m.