Triple
T19388325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purmerend |
E484991
|
entity |
| Predicate | hasMarket |
P2714
|
FINISHED |
| Object |
Koemarkt
Koemarkt is a central square in Purmerend, Netherlands, historically known as a cattle market and now a popular area with cafés, restaurants, and events.
|
E1374466
|
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: Koemarkt | Statement: [Purmerend, hasMarket, Koemarkt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koemarkt Context triple: [Purmerend, hasMarket, Koemarkt]
-
A.
Nieuwmarkt
Nieuwmarkt is a historic square and lively neighborhood in central Amsterdam known for its markets, cafés, and the medieval Waag building.
-
B.
Koornmarkt
Koornmarkt is a historic market square in the Dutch city of Kampen, traditionally associated with the grain trade.
-
C.
Noordermarkt
Noordermarkt is a historic square and popular market in Amsterdam’s Jordaan district, known for its organic farmers’ market and antique stalls.
-
D.
Heumarkt
Heumarkt is a historic square in Cologne’s Old Town known as a central marketplace and event space surrounded by notable landmarks, shops, and restaurants.
-
E.
Obermarkt
Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
- 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: Koemarkt Triple: [Purmerend, hasMarket, Koemarkt]
Generated description
Koemarkt is a central square in Purmerend, Netherlands, historically known as a cattle market and now a popular area with cafés, restaurants, and events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Koemarkt Target entity description: Koemarkt is a central square in Purmerend, Netherlands, historically known as a cattle market and now a popular area with cafés, restaurants, and events.
-
A.
Nieuwmarkt
Nieuwmarkt is a historic square and lively neighborhood in central Amsterdam known for its markets, cafés, and the medieval Waag building.
-
B.
Koornmarkt
Koornmarkt is a historic market square in the Dutch city of Kampen, traditionally associated with the grain trade.
-
C.
Noordermarkt
Noordermarkt is a historic square and popular market in Amsterdam’s Jordaan district, known for its organic farmers’ market and antique stalls.
-
D.
Heumarkt
Heumarkt is a historic square in Cologne’s Old Town known as a central marketplace and event space surrounded by notable landmarks, shops, and restaurants.
-
E.
Obermarkt
Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b425e848190ab5ae8ae0a034fe2 |
completed | April 20, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a072b8503108190bfcd0ac7c94183f7 |
completed | May 15, 2026, 2:19 p.m. |
| NEDg | Description generation | batch_6a072dc9e9808190ab0e5b6dd35147ab |
completed | May 15, 2026, 2:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a072e3709e881909d70f130a77fc428 |
completed | May 15, 2026, 2:31 p.m. |
Created at: April 10, 2026, 1:36 p.m.