Triple
T8666586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayta Darell |
E205689
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Toran Darell I |
E201000
|
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: Toran Darell I | Statement: [Bayta Darell, relative, Toran Darell I]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toran Darell I Context triple: [Bayta Darell, relative, Toran Darell I]
-
A.
Toran Darell
chosen
Toran Darell is a central character in Isaac Asimov's Foundation series, notably appearing as a key figure in the novel "Foundation and Empire."
-
B.
King Tahj
King Tahj is a music producer known for his work on the album "Songs About Girls."
-
C.
Trandal
Trandal is a small, scenic village in western Norway, known for its dramatic fjord landscape and location along the Hjørundfjord.
-
D.
Rasalhague
Rasalhague is the brightest star in the constellation Ophiuchus, representing the head of the serpent-bearer in the night sky.
-
E.
Ban Saladan
Ban Saladan is a small coastal town on Ko Lanta in Thailand that serves as the island’s main gateway and commercial hub for visitors to Mu Ko Lanta National Park.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a1dd1481908c56abca48fcd562 |
completed | March 31, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3898bf88190959b361638d032de |
completed | April 2, 2026, 10:54 p.m. |
Created at: March 30, 2026, 6:31 p.m.