Triple
T4446386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glomma |
E96298
|
entity |
| Predicate | tributary |
P415
|
FINISHED |
| Object | Vorma |
E421021
|
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: Vorma | Statement: [Glomma, tributary, Vorma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vorma Context triple: [Glomma, tributary, Vorma]
-
A.
Vorma
chosen
Vorma is a river in southeastern Norway that flows from Lake Mjøsa to the Glomma River and passes through the town of Eidsvoll.
-
B.
Formoza
Formoza is an elite Polish naval special operations unit renowned for maritime counter-terrorism, reconnaissance, and high-risk combat missions.
-
C.
Zima
Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
-
D.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
E.
Sikuani
The Sikuani are an Indigenous people of the Colombian and Venezuelan Llanos, known for their semi-nomadic traditions, rich oral culture, and Guahiboan language.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d1eba08190899d0a3c1684ce4e |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b613850eb88190b689a632b0e2b374 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:32 p.m.