Triple
T16089748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dejvická |
E390329
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Dejvice |
E968098
|
NE 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: Dejvice | Statement: [Dejvická, locatedIn, Dejvice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dejvice Context triple: [Dejvická, locatedIn, Dejvice]
-
A.
Dejvice
chosen
Dejvice is a prominent residential and university district in Prague known for its modernist architecture, green spaces, and the campus of the Czech Technical University.
-
B.
Dejvická
Dejvická is a metro station in Prague that serves as a key transport hub in the Dejvice district.
-
C.
Velké Poříčí
Velké Poříčí is a municipality and village in the Hradec Králové Region of the Czech Republic, situated near the town of Náchod close to the Polish border.
-
D.
Jindřišská
Jindřišská is a central Prague street known for connecting Wenceslas Square with the historic Jindřišská Tower and serving as a major tram and traffic route in the city center.
-
E.
Vávrová
Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1845161908190adca2af94710b2cc |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff29bc7408190be09bec1619b599c |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 4:59 a.m.