Triple
T12046457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghent Festival |
E286798
|
entity |
| Predicate | mainVenue |
P373
|
FINISHED |
| Object |
Korenmarkt
Korenmarkt is a central square in Ghent, Belgium, known as a major social and cultural hub that hosts key events and gatherings.
|
E961564
|
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: Korenmarkt | Statement: [Ghent Festival, mainVenue, Korenmarkt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korenmarkt Context triple: [Ghent Festival, mainVenue, Korenmarkt]
-
A.
Neuer Markt
Neuer Markt is a historic square in central Vienna, Austria, known for its baroque architecture, notable fountains, and surrounding churches and palaces.
-
B.
Marktl
Marktl is a small Bavarian municipality best known as the birthplace of Pope Benedict XVI.
-
C.
Marktbreit
Marktbreit is a small historic town in Bavaria, Germany, best known as the birthplace of psychiatrist and neuropathologist Alois Alzheimer.
-
D.
Karmelitermarkt
Karmelitermarkt is a popular neighborhood market in Vienna known for its fresh produce, specialty foods, and lively café culture.
-
E.
Markt
Markt is the central market square of Bruges, Belgium, known for its historic guild houses, bustling cafes, and prominent Belfry tower.
- 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: Korenmarkt Triple: [Ghent Festival, mainVenue, Korenmarkt]
Generated description
Korenmarkt is a central square in Ghent, Belgium, known as a major social and cultural hub that hosts key events and gatherings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Korenmarkt Target entity description: Korenmarkt is a central square in Ghent, Belgium, known as a major social and cultural hub that hosts key events and gatherings.
-
A.
Neuer Markt
Neuer Markt is a historic square in central Vienna, Austria, known for its baroque architecture, notable fountains, and surrounding churches and palaces.
-
B.
Marktl
Marktl is a small Bavarian municipality best known as the birthplace of Pope Benedict XVI.
-
C.
Marktbreit
Marktbreit is a small historic town in Bavaria, Germany, best known as the birthplace of psychiatrist and neuropathologist Alois Alzheimer.
-
D.
Karmelitermarkt
Karmelitermarkt is a popular neighborhood market in Vienna known for its fresh produce, specialty foods, and lively café culture.
-
E.
Markt
Markt is the central market square of Bruges, Belgium, known for its historic guild houses, bustling cafes, and prominent Belfry tower.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49db574bc8190a0f2f858a2ff788d |
completed | May 1, 2026, 12:33 p.m. |
| NEDg | Description generation | batch_69f53d95d4fc8190b5f4e460646bec2a |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564b826ec819098906cf735e45093 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.