Triple
T2223362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quincy Douby |
E48191
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Douby
Douby is the surname of Quincy Douby, a former professional basketball player who competed in the NBA and internationally.
|
E246040
|
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: Douby | Statement: [Quincy Douby, familyName, Douby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Douby Context triple: [Quincy Douby, familyName, Douby]
-
A.
Mulde
The Mulde is a river in central Germany that flows through the state of Saxony and is formed by the confluence of the Zwickauer Mulde and Freiberger Mulde.
-
B.
Dzvina
Dzvina is the Belarusian name for the Daugava River, a major Eastern European river flowing through Russia, Belarus, and Latvia into the Baltic Sea.
-
C.
Mirow
Mirow is a small historic town in the Mecklenburg Lake District of northeastern Germany, known for its castle island and connections to the House of Mecklenburg-Strelitz.
-
D.
Skawina
Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
-
E.
Jever
Jever is a historic town in Lower Saxony, Germany, best known for its traditional North German architecture and the Jever Pilsener brewery.
- 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: Douby Triple: [Quincy Douby, familyName, Douby]
Generated description
Douby is the surname of Quincy Douby, a former professional basketball player who competed in the NBA and internationally.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Douby Target entity description: Douby is the surname of Quincy Douby, a former professional basketball player who competed in the NBA and internationally.
-
A.
Mulde
The Mulde is a river in central Germany that flows through the state of Saxony and is formed by the confluence of the Zwickauer Mulde and Freiberger Mulde.
-
B.
Dzvina
Dzvina is the Belarusian name for the Daugava River, a major Eastern European river flowing through Russia, Belarus, and Latvia into the Baltic Sea.
-
C.
Mirow
Mirow is a small historic town in the Mecklenburg Lake District of northeastern Germany, known for its castle island and connections to the House of Mecklenburg-Strelitz.
-
D.
Skawina
Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
-
E.
Jever
Jever is a historic town in Lower Saxony, Germany, best known for its traditional North German architecture and the Jever Pilsener brewery.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03d1df88190950c691a4c246bd1 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6562c9448190b53c068c900bf0bf |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae667dede88190b3d1f8bb8866e19e |
completed | March 9, 2026, 6:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae66f12c648190a146de7b2bfdb541 |
completed | March 9, 2026, 6:21 a.m. |
Created at: March 4, 2026, 7:47 p.m.