Triple
T12927634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USM Auriga |
E309283
|
entity |
| Predicate | notablePassenger |
P881
|
FINISHED |
| Object | Johner |
E309277
|
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: Johner | Statement: [USM Auriga, notablePassenger, Johner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johner Context triple: [USM Auriga, notablePassenger, Johner]
-
A.
Johner
chosen
Johner is a wisecracking mercenary and crew member of the spaceship Betty in the science fiction horror film "Alien: Resurrection," portrayed by actor Ron Perlman.
-
B.
Joner
"Joner" is a poetry collection by Swedish poet Katarina Frostenson, known for its dense, experimental language and exploration of identity and perception.
-
C.
Jungmann
Jungmann is the nickname of the Bücker Bü 131, a German 1930s biplane widely used as a primary trainer aircraft before and during World War II.
-
D.
Joha
"Joha" is a popular Afrobeats track by Nigerian singer Asake, known for its catchy rhythm and street-influenced sound.
-
E.
Jost
Jost is a surname and given name of Germanic origin, used in various European countries and among their diasporas.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af6655e88190ac33567870a947bb |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:42 p.m.