Triple
T6133606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leopoldstadt |
E136778
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Simmering |
E287426
|
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: Simmering | Statement: [Leopoldstadt, borderedBy, Simmering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simmering Context triple: [Leopoldstadt, borderedBy, Simmering]
-
A.
Simmering
chosen
Simmering is the 11th district of Vienna, Austria, known for its mix of industrial areas, residential neighborhoods, and major sites such as the Vienna Central Cemetery.
-
B.
Boiling Pot
Boiling Pot is a turbulent section of the Zambezi River below Victoria Falls, known for its powerful whirlpools and dramatic gorge scenery.
-
C.
Tiepido
Tiepido is a small river in northern Italy that serves as a tributary of the Panaro River.
-
D.
Boiling Point
Boiling Point is a British drama film starring Stephen Graham as a head chef struggling through an intensely pressured service in a single-take narrative.
-
E.
Kuřim
Kuřim is a small industrial town in the South Moravian Region of the Czech Republic, located just northwest of Brno.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c7f34d081909e589b201b22be21 |
completed | March 22, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135dcace481909b60c1816179f78a |
completed | March 23, 2026, 12:45 p.m. |
Created at: March 22, 2026, 4:15 p.m.