Triple
T4821191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Metropolis of Lille |
E107712
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object |
Loos
Loos is a commune in northern France that forms part of the Lille metropolitan area.
|
E472561
|
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: Loos | Statement: [European Metropolis of Lille, includesCity, Loos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loos Context triple: [European Metropolis of Lille, includesCity, Loos]
-
A.
Breda
Breda is an Italian industrial company best known for manufacturing railway rolling stock, including trains and trams used in transit systems worldwide.
-
B.
Breda
Breda is a historic city in the southern Netherlands known for its medieval architecture, former status as a military and political center, and vibrant cultural life.
-
C.
Knokke-Heist
Knokke-Heist is a Belgian coastal resort town known for its beaches, upscale tourism, and proximity to the Dutch border.
-
D.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
E.
Machelen
Machelen is a municipality in the Belgian province of Flemish Brabant, located just northeast of Brussels and known for its mix of residential areas and business zones near the capital.
- 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: Loos Triple: [European Metropolis of Lille, includesCity, Loos]
Generated description
Loos is a commune in northern France that forms part of the Lille metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loos Target entity description: Loos is a commune in northern France that forms part of the Lille metropolitan area.
-
A.
Breda
Breda is an Italian industrial company best known for manufacturing railway rolling stock, including trains and trams used in transit systems worldwide.
-
B.
Breda
Breda is a historic city in the southern Netherlands known for its medieval architecture, former status as a military and political center, and vibrant cultural life.
-
C.
Knokke-Heist
Knokke-Heist is a Belgian coastal resort town known for its beaches, upscale tourism, and proximity to the Dutch border.
-
D.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
E.
Machelen
Machelen is a municipality in the Belgian province of Flemish Brabant, located just northeast of Brussels and known for its mix of residential areas and business zones near the capital.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c99b46c8190b6fbcf9f98b9e993 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4dc3cf5c8190bcd6ef039bab9878 |
completed | March 21, 2026, 7:50 a.m. |
| NEDg | Description generation | batch_69be4e8385e08190a46b1e129234c884 |
completed | March 21, 2026, 7:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be4f27f5a48190b639c9212e46f21d |
completed | March 21, 2026, 7:56 a.m. |
Created at: March 20, 2026, 1:24 p.m.