Triple
T16310353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Armisen |
E396038
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Armisen |
E396038
|
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: Armisen | Statement: [Fred Armisen, familyName, Armisen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Armisen Context triple: [Fred Armisen, familyName, Armisen]
-
A.
Armisen
chosen
Armisen is the surname of Fred Armisen, an American comedian, actor, writer, and musician known for his work on Saturday Night Live and Portlandia.
-
B.
Aramm
Aramm is a 2017 Tamil social drama film starring Nayanthara as a dedicated district collector tackling a village water crisis and systemic negligence.
-
C.
Asen
Asen was a medieval Bulgarian noble and co-leader, with his brother Peter, of the uprising that restored the Second Bulgarian Empire in the late 12th century.
-
D.
Ayrum
Ayrum is a small town in northeastern Armenia known for its location near the Georgian border and its role as a local transport and trade hub.
-
E.
Armant
Armant is a city in Egypt’s Luxor Governorate, known for its ancient Egyptian heritage and archaeological sites.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288da27f88190aa241e3addf9cd7f |
completed | April 17, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa6ceb48190b937a15b94fd3cfa |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.