Triple
T2144925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gavere-Semmerzake |
E47041
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Semmerzake
Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
|
E236974
|
NE FINISHED |
How this triple was built (4 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: [Gavere-Semmerzake, locatedIn, Semmerzake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semmerzake Context triple: [Gavere-Semmerzake, locatedIn, Semmerzake]
-
A.
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.
-
B.
Brocken
Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
-
C.
Nadelhorn
Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing routes.
-
D.
Seebruck
Seebruck is a Bavarian lakeside village and popular holiday resort on the northern shore of Lake Chiemsee in southern Germany.
-
E.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Semmerzake Triple: [Gavere-Semmerzake, locatedIn, Semmerzake]
Generated description
Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Semmerzake Target entity description: Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
-
A.
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.
-
B.
Brocken
Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
-
C.
Nadelhorn
Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing routes.
-
D.
Seebruck
Seebruck is a Bavarian lakeside village and popular holiday resort on the northern shore of Lake Chiemsee in southern Germany.
-
E.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
- F. None of above. chosen
Provenance (5 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe243e248190848bb1b86047f980 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51b8152c81908c66d389bf14dc7e |
completed | March 9, 2026, 4:51 a.m. |
| NEDg | Description generation | batch_69ae522f0394819087a7e7d9c6ca354c |
completed | March 9, 2026, 4:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5316acf881908dde9d83c36c8fd0 |
completed | March 9, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:44 p.m.