Triple
T6475233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Ostbahnhof |
E146053
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Spree River |
E513539
|
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: Spree River | Statement: [Berlin Ostbahnhof, locatedNear, Spree River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spree River Context triple: [Berlin Ostbahnhof, locatedNear, Spree River]
-
A.
Spree River
chosen
The Spree River is a major waterway in eastern Germany that flows through Berlin, shaping the city’s landscape and hosting many of its most prominent landmarks.
-
B.
Plenty River
The Plenty River is a waterway in Victoria, Australia, that flows through Melbourne’s northeastern suburbs before joining the Yarra River.
-
C.
Tüp River
The Tüp River is a mountain river in northeastern Kyrgyzstan that flows into Lake Issyk-Kul, contributing to the lake’s freshwater inflow.
-
D.
Eerste River
Eerste River is a prominent waterway in South Africa’s Western Cape that flows through the Stellenbosch region and supports its agriculture and ecosystems.
-
E.
Innerste River
The Innerste River is a tributary of the Leine in Lower Saxony, Germany, flowing through the Hildesheim region and contributing to the historic landscape around the city’s famed medieval churches.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a341360819082f2b5496a1a68b0 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dbc697388190b384c7ed9e6a65dc |
completed | April 10, 2026, 11:15 a.m. |
Created at: March 22, 2026, 4:50 p.m.