Triple
T13881168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferenc Molnár |
E333719
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ferenc |
E378878
|
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: Ferenc | Statement: [Ferenc Molnár, givenName, Ferenc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferenc Context triple: [Ferenc Molnár, givenName, Ferenc]
-
A.
Ferenc
chosen
Ferenc is a Hungarian masculine given name, equivalent to Francis in English.
-
B.
László
László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
-
C.
Miklós
Miklós is a Hungarian masculine given name, equivalent to Nicholas in English.
-
D.
József
József is a Hungarian masculine given name equivalent to Joseph, commonly used in Hungary and among Hungarian communities.
-
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 (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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be8566881908b8902e3cd567669 |
completed | April 14, 2026, 9:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc31c38e481909a86cda6c913fb8e |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:15 p.m.