Triple
T8017774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Göppingen district |
E186661
|
entity |
| Predicate | traversedByRiver |
P165
|
FINISHED |
| Object | Rems |
E384949
|
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: Rems | Statement: [Göppingen district, traversedByRiver, Rems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rems Context triple: [Göppingen district, traversedByRiver, Rems]
-
A.
Rems
chosen
The Rems is a river in the German state of Baden-Württemberg that flows through the Swabian Jura and into the Neckar.
-
B.
REMS
REMS is a meteorological instrument suite on NASA's Curiosity rover that measures Martian weather and atmospheric conditions.
-
C.
Remm
Remm is a Japanese hotel brand known for its compact, design-focused “sleep-centric” business hotels operated by Hankyu Hanshin Hotels.
-
D.
Eminado
Eminado is a popular Afrobeat song by Nigerian singer Tiwa Savage, known for its catchy melody and romantic lyrics.
-
E.
Remo
Remo is a prominent Yoruba sub-group in southwestern Nigeria, historically centered in present-day Ogun State and known for its rich cultural and political heritage.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df4f1b8819089a8b67f136bce9a |
completed | March 31, 2026, 3:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56c213ec8190b3bd96c42d1357e4 |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:20 p.m.