Triple
T12697906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet Colonel Zaysen |
E303383
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Marc de Jonge |
E302334
|
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: Marc de Jonge | Statement: [Soviet Colonel Zaysen, portrayedBy, Marc de Jonge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marc de Jonge Context triple: [Soviet Colonel Zaysen, portrayedBy, Marc de Jonge]
-
A.
Marc de Jonge
chosen
Marc de Jonge was a French actor best known internationally for playing the Soviet Colonel Zaysen in the action film "Rambo III."
-
B.
Sander van Doorn
Sander van Doorn is a Dutch DJ and electronic music producer known for his influential work in trance and progressive house.
-
C.
Lucas Conijn
Lucas Conijn was a 17th-century Dutch militia officer portrayed as a key figure in Frans Hals’s group portrait “The Company of Captain Albert Bas and Lieutenant Lucas Conijn.”
-
D.
Martin Dekker
Martin Dekker is a fictional character appearing in the Doctor Who audio drama "The Silence."
-
E.
Adrian Sweere
Adrian Sweere was an early 20th-century Jesuit priest and educator who played a key role in establishing what would become Seattle University.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ed26588190ae76ff17159e06ec |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671b066348190aedfe186fc4724f9 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:22 p.m.