Triple
T5432022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | golden throne of Hera |
E121517
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Olympus |
E316971
|
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: Olympus | Statement: [golden throne of Hera, location, Olympus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olympus Context triple: [golden throne of Hera, location, 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.
Nister
The Nister is a river in western Germany, known as a scenic tributary of the Sieg that flows through the Westerwald region.
-
C.
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.
-
D.
Canazei
Canazei is a mountain village and ski resort in the Dolomites of northern Italy, known for winter sports and alpine tourism.
-
E.
Shumshu
Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd883f982c8190bdf277e1ba85ff7b |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac985e48190ba9610e0563c73ab |
completed | March 22, 2026, 12:41 a.m. |
Created at: March 20, 2026, 2:06 p.m.