Triple
T3327429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François Hemony |
E69948
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Deventer |
E360206
|
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: Deventer | Statement: [François Hemony, workLocation, Deventer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deventer Context triple: [François Hemony, workLocation, Deventer]
-
A.
Deventer
chosen
Deventer is a historic Dutch city known for its medieval architecture, Hanseatic trading past, and annual book market.
-
B.
Culemborg
Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
-
C.
Zutphen
Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
-
D.
Zwolle
Zwolle is a historic Dutch city in the eastern Netherlands known for its medieval center, cultural heritage, and regional economic importance.
-
E.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
- 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb16f61248190bab10f4ac9e066f7 |
completed | March 8, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3667a288190aa79835f5d621942 |
completed | March 14, 2026, 2:09 a.m. |
Created at: March 8, 2026, 3:12 p.m.