Triple
T8787997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allgäu |
E209089
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Iller |
E197465
|
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: Iller | Statement: [Allgäu, hasRiver, Iller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iller Context triple: [Allgäu, hasRiver, Iller]
-
A.
Iller
chosen
The Iller is a river in southern Germany that flows through Bavaria and Baden-Württemberg before joining the Danube.
-
B.
Illiyyin
Illiyyin is an exalted register in Islamic belief that records the deeds and status of the righteous in the highest realms of heaven.
-
C.
Iller valley
The Iller valley is a river valley in southern Germany shaped by the Iller River, known for its rural landscapes, small towns, and agricultural areas.
-
D.
Lakelands
Lakelands is a New Urbanist-style planned residential community in Gaithersburg, Maryland, known for its walkable streets, mixed-use design, and small-town feel.
-
E.
Rock Island
Rock Island is a small, remote island in Lake Michigan known for its state park, historic lighthouse, and rustic natural setting accessible only by boat.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f89a84c819085d4cfe4e6dfbda8 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf520678f48190a0af3df75df9b269 |
completed | April 3, 2026, 5:37 a.m. |
Created at: March 30, 2026, 6:43 p.m.