Triple
T8022849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MotorSport |
E186778
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Joshua Luellen |
E707766
|
NE FINISHED |
How this triple was built (2 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: Joshua Luellen | Statement: [MotorSport, writer, Joshua Luellen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joshua Luellen Context triple: [MotorSport, writer, Joshua Luellen]
-
A.
Joshua Luellen
chosen
Joshua Luellen, better known as Southside, is an American record producer and songwriter recognized for his influential work in trap music and collaborations with major hip-hop artists.
-
B.
Joshua Gomez
Joshua Gomez is an American actor best known for his role as Morgan Grimes on the television series "Chuck."
-
C.
Joshua Kraft
Joshua Kraft is a member of the prominent Kraft family, known for their leadership of the New England Patriots and extensive business and philanthropic activities.
-
D.
Joshua Bowman
Joshua Bowman is a British actor best known for his role as Daniel Grayson on the television drama series "Revenge."
-
E.
Daniel Lugo
Daniel Lugo is the ambitious, bodybuilding ringleader of the criminal scheme at the center of the dark comedy crime film "Pain & Gain."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8fb6788190a16413051ec26988 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63c6a9208190841ed55b8c6ec73f |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:21 p.m.