Triple
T3712441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhin |
E81445
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Neckar |
E79602
|
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: Neckar | Statement: [Rhin, hasTributary, Neckar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neckar Context triple: [Rhin, hasTributary, Neckar]
-
A.
Neckar
chosen
The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
-
B.
Kinzig
The Kinzig is a river in southwestern Germany that flows through the Black Forest region before joining the Rhine.
-
C.
Regnitz
The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
-
D.
High Rhine
The High Rhine is a stretch of the Rhine River in Central Europe, flowing swiftly between Lake Constance and Basel and forming part of the border between Germany and Switzerland.
-
E.
Saale
The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc9cbc5648190936f93868086167e |
completed | March 8, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b65f1304b481909715c263a743581d |
completed | March 15, 2026, 7:26 a.m. |
Created at: March 8, 2026, 3:33 p.m.