Triple
T5436945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddy Jeannette |
E122031
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Jeannette
Jeannette is a surname most notably associated with Buddy Jeannette, a prominent American professional basketball player and coach.
|
E519512
|
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: Jeannette | Statement: [Buddy Jeannette, familyName, Jeannette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeannette Context triple: [Buddy Jeannette, familyName, Jeannette]
-
A.
L’Enfant
L’Enfant is the surname of Pierre Charles L’Enfant, the French-born American architect and civil engineer best known for designing the basic plan for Washington, D.C.
-
B.
L’Enfant
"L’Enfant" is a contemplative instrumental track by Greek composer Vangelis, featured on his 1979 electronic album *Opera Sauvage* and later known for its use in film and television.
-
C.
Julie
Julie is a feminine given name of Latin origin, commonly used in many Western countries.
-
D.
Anita
Anita is a feminine given name used in various cultures, often as a diminutive of names like Ana or Anna.
-
E.
The Girl Who Had Everything
The Girl Who Had Everything is a 1953 American drama film starring Elizabeth Taylor as a young woman torn between her powerful lawyer father and a charismatic racketeer.
- 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: Jeannette Triple: [Buddy Jeannette, familyName, Jeannette]
Generated description
Jeannette is a surname most notably associated with Buddy Jeannette, a prominent American professional basketball player and coach.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jeannette Target entity description: Jeannette is a surname most notably associated with Buddy Jeannette, a prominent American professional basketball player and coach.
-
A.
L’Enfant
L’Enfant is the surname of Pierre Charles L’Enfant, the French-born American architect and civil engineer best known for designing the basic plan for Washington, D.C.
-
B.
L’Enfant
"L’Enfant" is a contemplative instrumental track by Greek composer Vangelis, featured on his 1979 electronic album *Opera Sauvage* and later known for its use in film and television.
-
C.
Julie
Julie is a feminine given name of Latin origin, commonly used in many Western countries.
-
D.
Anita
Anita is a feminine given name used in various cultures, often as a diminutive of names like Ana or Anna.
-
E.
The Girl Who Had Everything
The Girl Who Had Everything is a 1953 American drama film starring Elizabeth Taylor as a young woman torn between her powerful lawyer father and a charismatic racketeer.
- 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91bb51d48190aab340d8d25e9a9a |
completed | March 20, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3acfd0408190877fbe41f1dc45ba |
completed | March 22, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69bf3c4f3e288190bab81e761017f015 |
completed | March 22, 2026, 12:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf3cde5004819096988c61b45958ea |
completed | March 22, 2026, 12:50 a.m. |
Created at: March 20, 2026, 2:07 p.m.