Triple
T16081828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Age of Fishes |
E390127
|
entity |
| Predicate | paleogeography |
P3590
|
FINISHED |
| Object | Laurussia |
E415304
|
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: Laurussia | Statement: [Age of Fishes, paleogeography, Laurussia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurussia Context triple: [Age of Fishes, paleogeography, Laurussia]
-
A.
Laurussia
chosen
Laurussia, also known as Euramerica, was an ancient Paleozoic supercontinent formed by the collision of Laurentia, Baltica, and Avalonia that later played a key role in the assembly of Pangaea.
-
B.
Ladonia
Ladonia is a small unincorporated community located within Russell County, Alabama.
-
C.
Ladania
Ladania is a town located in the Madhubani district of the Indian state of Bihar.
-
D.
Landes
Landes is a department in southwestern France known for its vast Atlantic coastline, extensive pine forests, and popular surfing beaches.
-
E.
Mulgimaa
Mulgimaa is a historic cultural region in southern Estonia known for its distinct Mulgi dialect, traditional folk culture, and influential role in Estonian national awakening.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1844b86288190ad0452aad6bdd5fb |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe48cf76c8190bc96168fc2326ffb |
completed | May 10, 2026, 1:51 a.m. |
Created at: April 10, 2026, 4:57 a.m.