Triple
T3924089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Angels Take Manhattan |
E93230
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Alex Kingston |
E138803
|
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: Alex Kingston | Statement: [The Angels Take Manhattan, leadActor, Alex Kingston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Kingston Context triple: [The Angels Take Manhattan, leadActor, Alex Kingston]
-
A.
Alex Kingston
chosen
Alex Kingston is an English actress best known for her roles in the television series "ER" and "Doctor Who," as well as numerous film and stage productions.
-
B.
Erica Durance
Erica Durance is a Canadian actress best known for playing Lois Lane on the television series "Smallville."
-
C.
Lauren Cohan
Lauren Cohan is an American-British actress best known for playing Maggie Greene on the television series "The Walking Dead."
-
D.
Nathalie Emmanuel
Nathalie Emmanuel is a British actress best known for her roles as Missandei in "Game of Thrones" and Ramsey in the "Fast & Furious" film franchise.
-
E.
Alafair Burke
Alafair Burke is an American crime novelist, law professor, and former prosecutor known for her contemporary suspense novels and collaborations on bestselling mystery series.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeed7dacdc8190854ebc13db2d24bc |
completed | March 9, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53fefa46c8190a6a2e7d9e90d11dd |
completed | March 14, 2026, 11:01 a.m. |
Created at: March 9, 2026, 3:23 p.m.