Triple
T15968933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Löhne |
E387268
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Else |
E1186047
|
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: Else | Statement: [Löhne, hasRiver, Else]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Else Context triple: [Löhne, hasRiver, Else]
-
A.
Else
Else is a literary work by Norwegian realist author Alexander Kielland, reflecting his critical engagement with 19th-century social and moral issues.
-
B.
Else
chosen
Else is a small river in North Rhine-Westphalia, Germany, that flows through the town of Spenge and its surrounding region.
-
C.
If/Then
If/Then is a contemporary Broadway musical that follows a woman’s parallel life paths in New York City, featuring a pop-influenced score and a starring role for Idina Menzel.
-
D.
Then
"Then" is a romantic country ballad by Brad Paisley that reflects on the deepening love in a long-term relationship.
-
E.
the Other
The Other is a mysterious, near-mythical figure in Doctor Who lore, often portrayed as one of the founding Time Lords whose essence is linked to the Doctor’s own origins.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3c5a7d48190891e69314e67e9af |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:54 a.m.