Triple
T22771465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipal Council of Port Vila |
E563567
|
entity |
| Predicate | locatedInTimeZone |
P109
|
FINISHED |
| Object | VUT |
—
|
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: VUT | Statement: [Municipal Council of Port Vila, locatedInTimeZone, VUT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VUT Context triple: [Municipal Council of Port Vila, locatedInTimeZone, VUT]
-
A.
VUT
VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
-
B.
VUT
chosen
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
-
C.
VU
VU is the vehicle registration code used on license plates for vehicles registered in Vukovar-Srijem County, Croatia.
-
D.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
E.
VŠE
VŠE is the commonly used abbreviation for the University of Economics in Prague, a leading Czech institution specializing in economics and business studies.
- 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b5e77d081909ea58d55c240662c |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:27 p.m.