Triple
T16011338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ninjini |
E388342
|
entity |
| Predicate | variantOf |
P4680
|
FINISHED |
| Object | Ninjini |
E388342
|
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: Ninjini | Statement: [Ninjini, variantOf, Ninjini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ninjini Context triple: [Ninjini, variantOf, Ninjini]
-
A.
Ninjini
chosen
Ninjini is a mystical, genie-like Magic Skylander character from the Skylanders: Giants video game, known for wielding dual swords and emerging from her enchanted bottle.
-
B.
Nagoa
Nagoa is a village in North Goa, India, known for its proximity to popular Goan beaches and tourist areas.
-
C.
Kura
Kura is a town and local government area in northern Nigeria’s Kano State, known primarily for its role in regional agriculture and trade.
-
D.
Kura
Kura is a major river in the South Caucasus that flows through Turkey, Georgia, and Azerbaijan before emptying into the Caspian Sea.
-
E.
Nachi River
The Nachi River is a short but significant river in Wakayama Prefecture, Japan, known for feeding the famous Nachi Falls near the sacred Kumano Nachi Taisha shrine.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1829119648190aef5b5e84b26d898 |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf24a9d8819083d7b11d71442da6 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.