Triple
T6434821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonin |
E129866
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Anton |
E28227
|
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: Anton | Statement: [Antonin, relatedName, Anton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anton Context triple: [Antonin, relatedName, Anton]
-
A.
Anton
chosen
Anton is a masculine given name of Latin origin, commonly used in various European and Slavic countries.
-
B.
Andrei
Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
-
C.
Anatole
Anatole is the famously temperamental and gifted French chef employed by Aunt Dahlia in P. G. Wodehouse’s Jeeves and Wooster stories.
-
D.
Rodion
Rodion is a masculine given name of Slavic origin, most notably borne by Soviet military commander Rodion Malinovsky.
-
E.
Emil
Emil is a masculine given name used in various European languages, often associated with Latin and Germanic origins.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069415c3c8190b91bd12ae79edd26 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640efd490819084b3b67b3b0680b6 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:45 p.m.