Triple
T4365681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drammenselva |
E98765
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Lier
Lier is a municipality in Buskerud county, Norway, known for its agricultural landscapes and proximity to the city of Drammen.
|
E433544
|
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: Lier | Statement: [Drammenselva, flowsThrough, Lier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lier Context triple: [Drammenselva, flowsThrough, Lier]
-
A.
Lier
Lier is a historic Belgian city in the province of Antwerp, known for its picturesque medieval center, the Zimmer Tower, and its UNESCO-listed beguinage.
-
B.
Kortrijk
Kortrijk is a historic city in western Belgium known for its medieval architecture, textile industry heritage, and role in the Battle of the Golden Spurs.
-
C.
Antwerp
Antwerp is a major Belgian port city on the River Scheldt, renowned as a global center for the diamond trade and its historic Flemish art and architecture.
-
D.
Liège
Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
-
E.
Lille Europe
Lille Europe is a major high-speed railway station in Lille, France, serving international Eurostar and TGV services between the UK and continental Europe.
- 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: Lier Triple: [Drammenselva, flowsThrough, Lier]
Generated description
Lier is a municipality in Buskerud county, Norway, known for its agricultural landscapes and proximity to the city of Drammen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lier Target entity description: Lier is a municipality in Buskerud county, Norway, known for its agricultural landscapes and proximity to the city of Drammen.
-
A.
Lier
Lier is a historic Belgian city in the province of Antwerp, known for its picturesque medieval center, the Zimmer Tower, and its UNESCO-listed beguinage.
-
B.
Kortrijk
Kortrijk is a historic city in western Belgium known for its medieval architecture, textile industry heritage, and role in the Battle of the Golden Spurs.
-
C.
Antwerp
Antwerp is a major Belgian port city on the River Scheldt, renowned as a global center for the diamond trade and its historic Flemish art and architecture.
-
D.
Liège
Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
-
E.
Lille Europe
Lille Europe is a major high-speed railway station in Lille, France, serving international Eurostar and TGV services between the UK and continental Europe.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35200263081909bb326a4d7a8db99 |
completed | March 12, 2026, 11:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dbcbbd1881908eb9f0ea6b2fe16b |
completed | March 14, 2026, 10:06 p.m. |
| NEDg | Description generation | batch_69b5dcf36dfc8190847925dbed92c059 |
completed | March 14, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5ddad45b8819082ac7a3a9c5f2f07 |
completed | March 14, 2026, 10:14 p.m. |
Created at: March 12, 2026, 11:17 p.m.