Triple
T19020054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | children of Styx |
E465459
|
entity |
| Predicate | resideIn |
P75
|
FINISHED |
| Object | Olympus |
—
|
NE NERFINISHED |
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: Olympus | Statement: [children of Styx, resideIn, Olympus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olympus Context triple: [children of Styx, resideIn, Olympus]
-
A.
Olympus
chosen
Olympus is the highest and most famous mountain in Greece, revered in Greek mythology as the home of the Olympian gods.
-
B.
Olympus
Olympus is a Japanese manufacturer best known for its optical and imaging products, including cameras, lenses, and medical endoscopes.
-
C.
Akamas
Akamas is a figure from Greek mythology, known as the son of Theseus and a participant in the Trojan War.
-
D.
Nister
The Nister is a river in western Germany, known as a scenic tributary of the Sieg that flows through the Westerwald region.
-
E.
Oukaimeden
Oukaimeden is a popular ski resort and mountain destination in the High Atlas Mountains of Morocco, known for its winter sports and scenic alpine landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6ddc9608190a1daec9ddcc79a7a |
completed | April 20, 2026, 7:33 a.m. |
Created at: April 10, 2026, 12:02 p.m.