Triple
T21954908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Netolicky |
E542161
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Netolicky |
—
|
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: Netolicky | Statement: [Bob Netolicky, familyName, Netolicky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netolicky Context triple: [Bob Netolicky, familyName, Netolicky]
-
A.
Netolicky
chosen
Netolicky is the surname of Bob Netolicky, an American former professional basketball player known for his career in the American Basketball Association (ABA).
-
B.
Netolice
Netolice is a small historic town in the South Bohemian Region of the Czech Republic, known for its Renaissance architecture and proximity to the Kratochvíle chateau.
-
C.
Nete
The Nete is a river in Belgium that flows through the Flemish region and serves as one of the main tributaries forming the Rupel River.
-
D.
Netishyn
Netishyn is a small city in western Ukraine known primarily for hosting the Khmelnytskyi Nuclear Power Plant.
-
E.
Neto
Neto is a Brazilian contemporary artist known for his large-scale, immersive installations that often use stretchy fabrics and organic forms to engage viewers’ senses.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243f46dc819097e4a1849af7fba4 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:59 p.m.