Triple
T12105253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children of Eden |
E288284
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | land of Nod |
E489688
|
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: land of Nod | Statement: [Children of Eden, setting, land of Nod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: land of Nod Context triple: [Children of Eden, setting, land of Nod]
-
A.
land of Nod
chosen
The land of Nod is a mysterious region mentioned in the Bible as the place of Cain’s exile after he killed his brother Abel.
-
B.
Garden of Eden
The Garden of Eden is the biblical paradise where the first humans, Adam and Eve, lived in innocence before their expulsion.
-
C.
Eveless Eden
Eveless Eden is a novel by American author Marianne Wiggins that blends literary fiction with political and historical themes.
-
D.
Skyland
Skyland is a mountain resort area in Shenandoah National Park, Virginia, known for its scenic vistas along Skyline Drive.
-
E.
Dark Land
Dark Land is the final, lava-filled world ruled by Bowser in Super Mario Bros. 3, known for its high difficulty and fortress-heavy layout.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91561eaec819096ba00682d81f41a |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f677039481908f14fa12b9b86910 |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.