Triple
T4332505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uatsdin |
E97385
|
entity |
| Predicate | hasMajorDeity |
P7648
|
FINISHED |
| Object | Donbettyr |
E417311
|
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: Donbettyr | Statement: [Uatsdin, hasMajorDeity, Donbettyr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donbettyr Context triple: [Uatsdin, hasMajorDeity, Donbettyr]
-
A.
Donbettyr
chosen
Donbettyr is a deity in Ossetian folk religion, commonly associated with water, rivers, and aquatic realms.
-
B.
Le Tote
Le Tote is a fashion rental subscription service company that expanded into traditional retail by acquiring the historic department store chain Lord & Taylor.
-
C.
Judi
Judi is the given name of acclaimed English actress Dame Judi Dench, renowned for her work in theatre, film, and television.
-
D.
Mr. DOB
Mr. DOB is Takashi Murakami’s iconic cartoon-like character and recurring motif that blends Japanese pop culture with fine art in his Superflat style.
-
E.
Bonza
Bonza is an Australian low-cost airline known for operating domestic routes that connect regional and leisure destinations.
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3563eab24819088add9180af2ce3c |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d0a307388190af4cb98b03e9656d |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.