Triple
T21395273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D3 motorway |
E527762
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Tábor |
—
|
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: Tábor | Statement: [D3 motorway, passesNear, Tábor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tábor Context triple: [D3 motorway, passesNear, Tábor]
-
A.
Tábor
chosen
Tábor is a historic Czech town best known as a major stronghold and center of the radical Hussite movement in the early 15th century.
-
B.
Tuřany
Tuřany is a district of the Czech city of Brno, known for hosting the region’s main international airport.
-
C.
Tuchkovo
Tuchkovo is an urban-type settlement in Moscow Oblast, Russia, located west of Moscow and known for its proximity to the Ruza Reservoir and regional transport links.
-
D.
Turośl
Turośl is a village in northern Poland located within the Warmian-Masurian Voivodeship, a region known for its lakes and forests.
-
E.
Letohrad
Letohrad is a small town in the Pardubice Region of the Czech Republic, known for its historic center and location in the Orlické Mountains foothills.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62cd30f08190aba90afed6116a2a |
completed | April 26, 2026, 7:09 p.m. |
Created at: April 16, 2026, 5:13 p.m.