Triple
T26938468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miklošičeva Street |
E678447
|
entity |
| Predicate | namedAfterEponymNationality |
P158984
|
FINISHED |
| Object | Slovene |
—
|
LITERAL 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: Slovene | Statement: [Miklošičeva Street, namedAfterEponymNationality, Slovene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterEponymNationality Context triple: [Miklošičeva Street, namedAfterEponymNationality, Slovene]
-
A.
eponymKnownFor
Indicates that a person or entity is widely recognized or named as the source or inspiration for something else (such as a concept, place, or object).
-
B.
eponymCountry
Indicates that a country is named after (or serves as the namesake for) a particular person, place, or entity.
-
C.
eponymOriginCountry
chosen
Indicates the country from which the person or entity that gave its name (as an eponym) to something originates.
-
D.
eponymProfession
Indicates that a person’s profession is the source of an eponym, i.e., a word or name derived from that professional role.
-
E.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
- F. None of above.
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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 27, 2026, 6:17 a.m.