Triple
T5097078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alec Hardison |
E114891
|
entity |
| Predicate | worksWith |
P398
|
FINISHED |
| Object | Nathan Ford |
E98904
|
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: Nathan Ford | Statement: [Alec Hardison, worksWith, Nathan Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Ford Context triple: [Alec Hardison, worksWith, Nathan Ford]
-
A.
Nathan Ford
chosen
Nathan Ford is the brilliant but morally conflicted former insurance investigator who leads a team of thieves and con artists in the television series "Leverage."
-
B.
Nate Ford
Nate Ford is the brilliant but morally conflicted former insurance investigator who leads the crew of con artists in the television series "Leverage."
-
C.
Nathan Field
Nathan Field was a notable English Jacobean actor and playwright associated with the Children of the Queen's Revels and later the King's Men.
-
D.
Sam Ford
Sam Ford is the son of Nathan Ford, the central mastermind character from the television series "Leverage."
-
E.
Joe Sawyer
Joe Sawyer was a Canadian-born character actor known for his tough-guy roles in numerous American films and television shows from the 1930s through the 1960s.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75669afc81908a8db897fe56eccd |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba80aee081908498cbe9d4f2eaa7 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:40 p.m.