Triple
T19404505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mihály Vitéz Székely |
E485416
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mihály |
—
|
NE NERFINISHED |
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: Mihály | Statement: [Mihály Vitéz Székely, givenName, Mihály]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mihály Context triple: [Mihály Vitéz Székely, givenName, Mihály]
-
A.
Mihály
chosen
Mihály is a Hungarian given name commonly used as the equivalent of Michael in English.
-
B.
Miklós
Miklós is a Hungarian masculine given name, equivalent to Nicholas in English.
-
C.
József
József is a Hungarian masculine given name equivalent to Joseph, commonly used in Hungary and among Hungarian communities.
-
D.
László
László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
-
E.
Gábor
Gábor is a Hungarian masculine given name, commonly used as the local form of Gabriel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257a361c8190bf019fc350faa225 |
completed | April 20, 2026, 1:09 p.m. |
Created at: April 10, 2026, 1:36 p.m.