Triple
T6736172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Daneyko |
E153760
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Daneyko
Daneyko is the surname of Ken Daneyko, a longtime New Jersey Devils defenseman and three-time Stanley Cup champion in the National Hockey League.
|
E614951
|
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: Daneyko | Statement: [Ken Daneyko, familyName, Daneyko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daneyko Context triple: [Ken Daneyko, familyName, Daneyko]
-
A.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
B.
Dolgan
Dolgan is a Turkic language spoken primarily by the Dolgan people in northern Siberia, especially in Russia’s Taymyr Peninsula.
-
C.
Titarenko
Titarenko is a Ukrainian-origin surname most notably borne by Raisa Maksimovna, the wife of former Soviet leader Mikhail Gorbachev.
-
D.
Tsitska
Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
-
E.
Antoshka
Antoshka is a common Russian diminutive form of the male given name Anton, often used affectionately or informally.
- 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: Daneyko Triple: [Ken Daneyko, familyName, Daneyko]
Generated description
Daneyko is the surname of Ken Daneyko, a longtime New Jersey Devils defenseman and three-time Stanley Cup champion in the National Hockey League.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daneyko Target entity description: Daneyko is the surname of Ken Daneyko, a longtime New Jersey Devils defenseman and three-time Stanley Cup champion in the National Hockey League.
-
A.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
B.
Dolgan
Dolgan is a Turkic language spoken primarily by the Dolgan people in northern Siberia, especially in Russia’s Taymyr Peninsula.
-
C.
Titarenko
Titarenko is a Ukrainian-origin surname most notably borne by Raisa Maksimovna, the wife of former Soviet leader Mikhail Gorbachev.
-
D.
Tsitska
Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
-
E.
Antoshka
Antoshka is a common Russian diminutive form of the male given name Anton, often used affectionately or informally.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d18369d88190a73349075462202b |
completed | March 27, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b09b97c8190a5a538571b6909f0 |
completed | March 27, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69c70bda97f08190bc6dab7177341876 |
completed | March 27, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70c51e0148190be64afb56690b34f |
completed | March 27, 2026, 11:01 p.m. |
Created at: March 27, 2026, 2:09 p.m.