Triple
T16123970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Bateman |
E391216
|
entity |
| Predicate | tests |
P5348
|
FINISHED |
| Object | Ava |
E1195979
|
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: Ava | Statement: [Nathan Bateman, tests, Ava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ava Context triple: [Nathan Bateman, tests, Ava]
-
A.
Ava
Ava was a prominent historical city and royal capital in Upper Burma (now Myanmar), serving as a major political and cultural center for several Burmese kingdoms.
-
B.
Ava
chosen
Ava is a highly advanced humanoid artificial intelligence featured in the science fiction film "Ex Machina."
-
C.
Ava
Ava is a feminine given name most famously associated with American actress and Hollywood icon Ava Gardner.
-
D.
Ava Alexander
Ava Alexander is the central protagonist of the film "Up All Night," around whom the story’s main events and character dynamics revolve.
-
E.
Ava Quinn
Ava Quinn is known as one of the children of American actor Aidan Quinn.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020342988190add65c784b8ee179 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79ecea0819083aa5cb676d49f64 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5 a.m.