Triple
T15758710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Ghent |
E382036
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Melle
Melle is a municipality in the Belgian province of East Flanders, known for its historic town center and proximity to the city of Ghent.
|
E1175119
|
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: Melle | Statement: [Arrondissement of Ghent, contains, Melle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melle Context triple: [Arrondissement of Ghent, contains, Melle]
-
A.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
B.
Melle
Melle is a town in the German state of North Rhine-Westphalia, known for its location in the Osnabrück district and its mix of industrial and rural character.
-
C.
Morangis
Morangis is a commune in the southern suburbs of Paris, located in the Essonne department in the Île-de-France region of northern France.
-
D.
Biesmelle
Biesmelle is a small river in Belgium that serves as a tributary of the Sambre.
-
E.
Messel
Messel is a small German municipality in Hesse best known for the nearby Messel Pit, a UNESCO World Heritage fossil site renowned for its exceptionally preserved Eocene-era fossils.
- 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: Melle Triple: [Arrondissement of Ghent, contains, Melle]
Generated description
Melle is a municipality in the Belgian province of East Flanders, known for its historic town center and proximity to the city of Ghent.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Melle Target entity description: Melle is a municipality in the Belgian province of East Flanders, known for its historic town center and proximity to the city of Ghent.
-
A.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
B.
Melle
Melle is a town in the German state of North Rhine-Westphalia, known for its location in the Osnabrück district and its mix of industrial and rural character.
-
C.
Morangis
Morangis is a commune in the southern suburbs of Paris, located in the Essonne department in the Île-de-France region of northern France.
-
D.
Biesmelle
Biesmelle is a small river in Belgium that serves as a tributary of the Sambre.
-
E.
Messel
Messel is a small German municipality in Hesse best known for the nearby Messel Pit, a UNESCO World Heritage fossil site renowned for its exceptionally preserved Eocene-era fossils.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b35ea48190a758ee76a57b5451 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877311dc8190b55fe7ca5c0843da |
completed | May 9, 2026, 7:13 p.m. |
| NEDg | Description generation | batch_69ff881731ac8190baa3cea2c9b7975b |
completed | May 9, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff88cfbe388190b20c426b4c745f92 |
completed | May 9, 2026, 7:19 p.m. |
Created at: April 10, 2026, 4:47 a.m.