Triple
T3344590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jette campus |
E70339
|
entity |
| Predicate | municipality |
P852
|
FINISHED |
| Object | Jette |
E350909
|
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: Jette | Statement: [Jette campus, municipality, Jette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jette Context triple: [Jette campus, municipality, Jette]
-
A.
Jette
chosen
Jette is a municipality in the Brussels-Capital Region of Belgium, known for its residential character and educational institutions, including the Jette campus.
-
B.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
C.
Zahle
Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
-
D.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
E.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1f23008819084ea68b8431c50ab |
completed | March 8, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33426f73881908eb0759c47eb08d7 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:12 p.m.