Triple
T8431672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spooks |
E199127
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Lucas North |
E345859
|
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: Lucas North | Statement: [Spooks, mainCharacter, Lucas North]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucas North Context triple: [Spooks, mainCharacter, Lucas North]
-
A.
Lucas North
chosen
Lucas North is a central MI5 officer character in the British television spy drama "Spooks" (also known as "MI-5").
-
B.
Lucas Beauchamp
Lucas Beauchamp is a proud, defiant Black farmer and central character in William Faulkner’s fiction, most notably in the novel "Go Down, Moses."
-
C.
Lucas Barclay
Lucas Barclay is one of the children of acclaimed American television and film director Paris Barclay.
-
D.
Lucas Black
Lucas Black is an American actor best known for his roles in films such as "Sling Blade," "The Fast and the Furious: Tokyo Drift," and the football drama "Friday Night Lights."
-
E.
Sebastian Henshaw
Sebastian Henshaw is a suave and skilled British intelligence agent who becomes entangled in a chaotic international espionage adventure in the action-comedy film "The Spy Who Dumped Me."
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd1a4876c81908d5a708bb1f35683 |
completed | March 31, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce038902308190bff57c9ce14e72ed |
completed | April 2, 2026, 5:50 a.m. |
Created at: March 30, 2026, 6:07 p.m.