Triple
T10313019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ochota campus |
E241943
|
entity |
| Predicate | locatedInDistrict |
P40
|
FINISHED |
| Object | Ochota |
E830443
|
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: Ochota | Statement: [Ochota campus, locatedInDistrict, Ochota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ochota Context triple: [Ochota campus, locatedInDistrict, Ochota]
-
A.
Mokotów
Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
-
B.
Wola Okrzejska
Wola Okrzejska is a village in eastern Poland best known as the birthplace of Nobel Prize–winning novelist Henryk Sienkiewicz.
-
C.
Okęcie
Okęcie is a district in Warsaw, Poland, best known for hosting the city’s main international airport and various aviation-related facilities.
-
D.
Ochota, Warsaw
chosen
Ochota is a central district of Warsaw known for its residential character, pre-war architecture, and proximity to the city’s downtown area.
-
E.
Wola district
Wola district is a central borough of Warsaw, Poland, known for its historical significance, rapid postwar development, and mix of industrial heritage with modern urban infrastructure.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d35a292c8190bc8c467e522bba92 |
completed | April 7, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7502f7b308190aaefd62f2f8a0ac3 |
completed | April 9, 2026, 7:07 a.m. |
Created at: April 6, 2026, 11:48 a.m.