Triple
T7792670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werre |
E180218
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Lage
Lage is a town in the Lippe district of North Rhine-Westphalia, Germany, known for its location in the Teutoburg Forest region.
|
E693910
|
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: Lage | Statement: [Werre, flowsThrough, Lage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lage Context triple: [Werre, flowsThrough, Lage]
-
A.
Lage
Lage is the surname of Carlos Lage Dávila, a prominent Cuban politician who served as Vice President of the Council of State and was considered a key figure in the country’s government in the early 2000s.
-
B.
Lage Landen
Lage Landen is the historical Low Countries region in Western Europe, roughly encompassing present-day Belgium, the Netherlands, and Luxembourg.
-
C.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
D.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
E.
Lapseki
Lapseki is a town and district in Çanakkale Province in northwestern Turkey, situated on the Asian shore of the Dardanelles Strait.
- 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: Lage Triple: [Werre, flowsThrough, Lage]
Generated description
Lage is a town in the Lippe district of North Rhine-Westphalia, Germany, known for its location in the Teutoburg Forest region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lage Target entity description: Lage is a town in the Lippe district of North Rhine-Westphalia, Germany, known for its location in the Teutoburg Forest region.
-
A.
Lage
Lage is the surname of Carlos Lage Dávila, a prominent Cuban politician who served as Vice President of the Council of State and was considered a key figure in the country’s government in the early 2000s.
-
B.
Lage Landen
Lage Landen is the historical Low Countries region in Western Europe, roughly encompassing present-day Belgium, the Netherlands, and Luxembourg.
-
C.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
D.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
E.
Lapseki
Lapseki is a town and district in Çanakkale Province in northwestern Turkey, situated on the Asian shore of the Dardanelles Strait.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae938714c8190b89917e6ded004da |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb13cdb4288190ae3cfe1ee4e3e496 |
completed | March 31, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69cb1636b0d48190a57c2d3a7b3b41ed |
completed | March 31, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a29d2988190bb64aada0d2ef463 |
completed | March 31, 2026, 12:49 a.m. |
Created at: March 30, 2026, 4:30 p.m.