Triple
T17264057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denderstreek |
E419077
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Erpe-Mere
Erpe-Mere is a municipality in the East Flanders province of Belgium, known for its rural character and location within the Denderstreek region.
|
E1259010
|
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: Erpe-Mere | Statement: [Denderstreek, hasPart, Erpe-Mere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erpe-Mere Context triple: [Denderstreek, hasPart, Erpe-Mere]
-
A.
Eemnes
Eemnes is a small town and municipality in the central Netherlands known for its characteristic polder landscape and historic village centers.
-
B.
Veddesta
Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
-
C.
Erna
Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
-
D.
Eivissa
Eivissa is the Catalan name for Ibiza, a popular Mediterranean island in Spain’s Balearic archipelago known for its beaches and nightlife.
-
E.
Longva
Longva is a small village in Norway’s Møre og Romsdal county, situated within the municipality of Haram on the island-dotted western coast.
- 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: Erpe-Mere Triple: [Denderstreek, hasPart, Erpe-Mere]
Generated description
Erpe-Mere is a municipality in the East Flanders province of Belgium, known for its rural character and location within the Denderstreek region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Erpe-Mere Target entity description: Erpe-Mere is a municipality in the East Flanders province of Belgium, known for its rural character and location within the Denderstreek region.
-
A.
Eemnes
Eemnes is a small town and municipality in the central Netherlands known for its characteristic polder landscape and historic village centers.
-
B.
Veddesta
Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
-
C.
Erna
Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
-
D.
Eivissa
Eivissa is the Catalan name for Ibiza, a popular Mediterranean island in Spain’s Balearic archipelago known for its beaches and nightlife.
-
E.
Longva
Longva is a small village in Norway’s Møre og Romsdal county, situated within the municipality of Haram on the island-dotted western coast.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4432fc81908fd90865822af1fa |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0171054f388190bf068ca2e6b88458 |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a0173faebf48190a1334a205cd9804a |
completed | May 11, 2026, 6:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0174a41204819097b9aeff2c09cffe |
completed | May 11, 2026, 6:18 a.m. |
Created at: April 10, 2026, 5:40 a.m.