Triple
T23358920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stu Ungar |
E593129
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ungar |
—
|
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: Ungar | Statement: [Stu Ungar, familyName, Ungar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ungar Context triple: [Stu Ungar, familyName, Ungar]
-
A.
Ungar
chosen
Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
-
B.
Ungarie
Ungarie is a small rural town in New South Wales, Australia, known for its agricultural community and location within the Bland Shire local government area.
-
C.
Hungarica
Hungarica refers to publications and documents related to Hungary or Hungarians, regardless of where they were produced.
-
D.
Hungary
Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
-
E.
Poroszló
Poroszló is a village in northern Hungary situated near Lake Tisza, known for its natural surroundings and eco-tourism opportunities.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a1a39988190b4b4993b80d5a5f6 |
completed | April 29, 2026, 5:41 a.m. |
Created at: April 17, 2026, 5:29 p.m.