Triple
T1998437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aligoté |
E43409
|
entity |
| Predicate | oftenBlendedWith |
P12771
|
FINISHED |
| Object |
Sacy
Sacy is a white grape variety from central France, historically used in light, crisp wines and blends, particularly in regions like Burgundy.
|
E223448
|
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: Sacy | Statement: [Aligoté, oftenBlendedWith, Sacy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sacy Context triple: [Aligoté, oftenBlendedWith, Sacy]
-
A.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
B.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
C.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
D.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
-
E.
Salamina
Salamina is a historic Colombian town in the Caldas Department, renowned for its well-preserved colonial architecture and coffee-growing heritage in the Andean region.
- 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: Sacy Triple: [Aligoté, oftenBlendedWith, Sacy]
Generated description
Sacy is a white grape variety from central France, historically used in light, crisp wines and blends, particularly in regions like Burgundy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sacy Target entity description: Sacy is a white grape variety from central France, historically used in light, crisp wines and blends, particularly in regions like Burgundy.
-
A.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
B.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
C.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
D.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
-
E.
Salamina
Salamina is a historic Colombian town in the Caldas Department, renowned for its well-preserved colonial architecture and coffee-growing heritage in the Andean region.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb867c49081909a9ca5fa21bf7aa3 |
completed | March 7, 2026, 5:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae033e733c8190aa11e316e01dbd17 |
completed | March 8, 2026, 11:16 p.m. |
| NEDg | Description generation | batch_69ae05c4c0b48190a2c063f991083ed9 |
completed | March 8, 2026, 11:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0731c56081909849263e12750ad6 |
completed | March 8, 2026, 11:33 p.m. |
Created at: March 4, 2026, 7:37 p.m.