Triple
T9765393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EBGT |
E236975
|
entity |
| Predicate | servesTown |
P847
|
FINISHED |
| Object | Semmerzake |
E236974
|
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: Semmerzake | Statement: [EBGT, servesTown, Semmerzake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semmerzake Context triple: [EBGT, servesTown, Semmerzake]
-
A.
Semmerzake
chosen
Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
-
B.
Heul
Heul is a small waterway in the Westland region of South Holland in the Netherlands, historically associated with the village of Kwintsheul and its surrounding polder landscape.
-
C.
Schneidhain
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
-
D.
Wilseder Berg
Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
-
E.
Hagetmau
Hagetmau is a small town in southwestern France’s Landes department, known for its rural character and traditional Gascon culture.
- 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_69d1bcf965e88190b505ce160f77e9b7 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:25 p.m.