Triple
T5553677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahnhofplatz Zürich |
E145585
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Limmat River |
E118490
|
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: Limmat River | Statement: [Bahnhofplatz Zürich, near, Limmat River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limmat River Context triple: [Bahnhofplatz Zürich, near, Limmat River]
-
A.
Limmat River
chosen
The Limmat River is a major Swiss waterway that flows out of Lake Zurich and runs through the city of Zurich before joining the Aare River.
-
B.
Pagladia River
Pagladia River is a tributary watercourse in northeastern India that feeds into the Manas River within the Brahmaputra river system.
-
C.
Uono River
The Uono River is a river in Niigata Prefecture, Japan, that flows through the Uonuma region before joining the Shinano River.
-
D.
Tuul River
The Tuul River is a major river in central Mongolia that flows through the capital city, Ulaanbaatar, and plays an important role in the region’s ecology and water supply.
-
E.
Olza River
The Olza River is a Central European river that flows through the historical region of Cieszyn Silesia, forming part of the border between Poland and the Czech Republic.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ff9c9c48190b5e587d58c6515d8 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecc01e1b88190817a73e580cf4f03 |
completed | April 2, 2026, 8:05 p.m. |
Created at: March 22, 2026, 3:35 p.m.