Triple
T11110553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Liège |
E262742
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Dalhem
Dalhem is a historic municipality in the province of Liège in eastern Belgium, known for its medieval heritage and rural character.
|
E905675
|
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: Dalhem | Statement: [Arrondissement of Liège, contains, Dalhem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dalhem Context triple: [Arrondissement of Liège, contains, Dalhem]
-
A.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
B.
Friesoythe
Friesoythe is a small town in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
-
C.
Rolandswerth
Rolandswerth is a district of the German town of Remagen, situated along the Rhine River in the state of Rhineland-Palatinate.
-
D.
Soest
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
-
E.
Soest
Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
- 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: Dalhem Triple: [Arrondissement of Liège, contains, Dalhem]
Generated description
Dalhem is a historic municipality in the province of Liège in eastern Belgium, known for its medieval heritage and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dalhem Target entity description: Dalhem is a historic municipality in the province of Liège in eastern Belgium, known for its medieval heritage and rural character.
-
A.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
B.
Friesoythe
Friesoythe is a small town in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
-
C.
Rolandswerth
Rolandswerth is a district of the German town of Remagen, situated along the Rhine River in the state of Rhineland-Palatinate.
-
D.
Soest
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
-
E.
Soest
Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a6964508190b679303d3b3a4fd6 |
completed | April 9, 2026, 12:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d759bc88190b670c373f3647a41 |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e4307baca48190bbf82f8235d7e2c7 |
completed | April 19, 2026, 1:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4375eaf448190a17f8df1e83145e0 |
completed | April 19, 2026, 2:01 a.m. |
Created at: April 8, 2026, 9:27 p.m.