Triple
T3004403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teylingen |
E81864
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sassenheim |
E458100
|
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: Sassenheim | Statement: [Teylingen, contains, Sassenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sassenheim Context triple: [Teylingen, contains, Sassenheim]
-
A.
Sassenheim
chosen
Sassenheim is a town in the Dutch province of South Holland, known historically for its bulb-growing industry and location within the Duin- en Bollenstreek (Dune and Bulb Region).
-
B.
Stadshagen
Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
-
C.
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.
-
D.
Scharendijke
Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
-
E.
Zutphen
Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a149b248190ac4f11afc4871cc1 |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfea8f024481908fdcded2ccb948e7 |
completed | March 22, 2026, 1:11 p.m. |
Created at: March 8, 2026, 2:59 p.m.