Triple
T10815472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heunisch Weiss |
E255216
|
entity |
| Predicate | parentOf |
P120
|
FINISHED |
| Object |
Orleans
Orleans is a white grape variety used in European wine production, historically cultivated in regions such as Germany and Central Europe.
|
E887598
|
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: Orleans | Statement: [Heunisch Weiss, parentOf, Orleans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orleans Context triple: [Heunisch Weiss, parentOf, Orleans]
-
A.
Orleans
Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
-
B.
Orléans
Orléans is a federal electoral district in the eastern part of Ottawa, Ontario, represented in the House of Commons of Canada.
-
C.
Orléans
Orléans is a historic city in north-central France, renowned for its association with Joan of Arc and its location on the Loire River.
-
D.
Saint-Louis
Saint-Louis is a French border town in the Alsace region, adjacent to Basel and known as a key cross-border transit and commuter hub between France, Switzerland, and Germany.
-
E.
Saint-Louis
Saint-Louis is a historic coastal city in northwestern Senegal that served as a major colonial administrative and trading center in French West Africa.
- 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: Orleans Triple: [Heunisch Weiss, parentOf, Orleans]
Generated description
Orleans is a white grape variety used in European wine production, historically cultivated in regions such as Germany and Central Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orleans Target entity description: Orleans is a white grape variety used in European wine production, historically cultivated in regions such as Germany and Central Europe.
-
A.
Orleans
Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
-
B.
Orléans
Orléans is a federal electoral district in the eastern part of Ottawa, Ontario, represented in the House of Commons of Canada.
-
C.
Orléans
Orléans is a historic city in north-central France, renowned for its association with Joan of Arc and its location on the Loire River.
-
D.
Saint-Louis
Saint-Louis is a French border town in the Alsace region, adjacent to Basel and known as a key cross-border transit and commuter hub between France, Switzerland, and Germany.
-
E.
Saint-Louis
Saint-Louis is a historic coastal city in northwestern Senegal that served as a major colonial administrative and trading center in French West Africa.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733edab248190b2cf7f7bc2684468 |
completed | April 9, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8546b41081909e13152c4df2eb1c |
completed | April 14, 2026, 6:19 p.m. |
| NEDg | Description generation | batch_69de8955b9d8819086ff98efbff6c7a0 |
completed | April 14, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de8f4a318c819086559fd53506ab29 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 8, 2026, 9:18 p.m.