Triple
T2948080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adrienne Nesser |
E79550
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Jakob Danger Armstrong |
E31888
|
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: Jakob Danger Armstrong | Statement: [Adrienne Nesser, relative, Jakob Danger Armstrong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jakob Danger Armstrong Context triple: [Adrienne Nesser, relative, Jakob Danger Armstrong]
-
A.
Jakob Danger Armstrong
chosen
Jakob Danger Armstrong is an American musician and the son of Green Day frontman Billie Joe Armstrong, known for his work in alternative and punk-influenced rock projects.
-
B.
Jeremiah Biggs
Jeremiah Biggs is the son of Reverend Henry Biggs, a clergyman known in his community for his religious leadership.
-
C.
Jack Napier
Jack Napier is the gangster who becomes the Joker, the primary antagonist in Tim Burton’s 1989 Batman film.
-
D.
Emmet Dalton
Emmet Dalton was an Irish soldier and revolutionary who served as a senior commander in the National Army during the Irish Civil War and later became a prominent film producer.
-
E.
Jeremiah Day
Jeremiah Day was an American academic who served as the long-time president of Yale College in the early 19th century.
- 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b6cab88190b4dee7e5ec9347e5 |
completed | March 8, 2026, 3:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc79f6d081908d3bbd52439f4d31 |
completed | March 11, 2026, 5:24 a.m. |
Created at: March 8, 2026, 2:57 p.m.