Triple
T23470143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iyaz |
E569203
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Solo |
—
|
NE NERFINISHED |
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: Solo | Statement: [Iyaz, notableWork, Solo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Solo Context triple: [Iyaz, notableWork, Solo]
-
A.
Solo
Solo is a city in Central Java, Indonesia, renowned as a major center of traditional Javanese culture and batik craftsmanship.
-
B.
Solo
"Solo" is a Cold War-era thriller novel by Jack Higgins that follows a notorious professional assassin whose latest mission spirals into a deadly international conspiracy.
-
C.
Solo
chosen
Solo is a 2018 Star Wars anthology film that explores the early adventures and origins of the iconic smuggler Han Solo.
-
D.
Solo
Solo is the surname of Hope Solo, the renowned American soccer goalkeeper and two-time Olympic gold medalist.
-
E.
Solo
Solo is a segment from the horror anthology film "The Turning," contributing one of its self-contained, eerie narrative episodes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6ff8dc0819086961b1f07030d9c |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.