Triple
T7654708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan Asselijn |
E173350
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jan Asselijn |
E173350
|
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: Jan Asselijn | Statement: [Jan Asselijn, name, Jan Asselijn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Asselijn Context triple: [Jan Asselijn, name, Jan Asselijn]
-
A.
Jan Asselijn
chosen
Jan Asselijn was a 17th-century Dutch Golden Age painter known for his landscapes and animal scenes, including the famous political allegory "The Threatened Swan."
-
B.
Dani van Velthoven
Dani van Velthoven is a Dutch singer who gained national fame after winning the popular televised talent competition The Voice of Holland.
-
C.
Jean van Duren
Jean van Duren was an 18th-century publisher known for issuing the political treatise "Anti-Machiavel," often associated with Frederick the Great.
-
D.
Jan D'Alquen
Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
-
E.
Bete Denagel
Bete Denagel is one of the rock-hewn monolithic churches in the historic Ethiopian town of Lalibela, renowned for its medieval Christian architecture and religious significance.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018d4cdc819092ca297b836190d9 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8de9d63908190b1adc84e5123b9c0 |
completed | March 29, 2026, 8:11 a.m. |
Created at: March 27, 2026, 3:59 p.m.