Triple
T9765395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EBGT |
E236975
|
entity |
| Predicate | locatedNearCity |
P3883
|
FINISHED |
| Object | Gavere |
E248431
|
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: Gavere | Statement: [EBGT, locatedNearCity, Gavere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gavere Context triple: [EBGT, locatedNearCity, Gavere]
-
A.
Gavere
chosen
Gavere is a municipality in the Belgian province of East Flanders, known for its rural character and several constituent villages.
-
B.
Gavere-Semmerzake
Gavere-Semmerzake is a Belgian military air base used by the Belgian Air Force.
-
C.
Veurne
Veurne is a historic town in western Belgium known for its well-preserved medieval center and Flemish Renaissance architecture.
-
D.
Zierikzee
Zierikzee is a historic Dutch town on the island of Schouwen-Duiveland in Zeeland, known for its well-preserved medieval center and maritime heritage.
-
E.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a040988190b1c940f9e5c42f9c |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc46f170819081ecc5e85a0514c3 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:25 p.m.