Triple
T22702035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Man on the Moon |
E561347
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Nena Danevic |
—
|
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: Nena Danevic | Statement: [Man on the Moon, editor, Nena Danevic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nena Danevic Context triple: [Man on the Moon, editor, Nena Danevic]
-
A.
Nena Danevic
chosen
Nena Danevic is a film editor best known for her Academy Award–winning work on the 1984 historical drama "Amadeus."
-
B.
Nataša Kandić
Nataša Kandić is a Serbian human rights activist known for documenting war crimes and advocating for justice and reconciliation in the former Yugoslavia.
-
C.
Neda Arnerić
Neda Arnerić was a prominent Serbian actress known for her extensive film and television career across Yugoslav and international cinema.
-
D.
Izabela Vidovic
Izabela Vidovic is a Bosnian-American actress known for her roles in films like "Homefront" and "Wonder" as well as various television series.
-
E.
Blanka Vlašić
Blanka Vlašić is a Croatian high jumper renowned for her multiple world titles and status as one of the greatest female high jumpers in athletics history.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cb2f548190bfc6f050be7c795a |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:16 p.m.