Triple
T18682233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holzwickede |
E456761
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | UN |
—
|
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: UN | Statement: [Holzwickede, vehicleRegistrationCode, UN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UN Context triple: [Holzwickede, vehicleRegistrationCode, UN]
-
A.
UN
The UN is an international organization founded in 1945 that brings together most of the world’s countries to promote peace, security, cooperation, and human rights.
-
B.
UN
chosen
UN is the vehicle registration code for the German town of Unna in the state of North Rhine-Westphalia.
-
C.
UNU
UNU is the United Nations University, a global think tank and postgraduate teaching organization of the UN system focused on research and capacity-building for sustainable development and peace.
-
D.
NU
NU is a leading Japanese national research university located in Nagoya, known for its strong programs in science, engineering, and the humanities.
-
E.
NU
NU is the official two-letter Canada Post abbreviation for the northern Canadian territory of Nunavut.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2906ec8190ad8db8e3ae6b2945 |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.