Triple
T16297916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Archer |
E395697
|
entity |
| Predicate | actedIn |
P1668
|
FINISHED |
| Object | Narrow Margin |
E498072
|
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: Narrow Margin | Statement: [Anne Archer, actedIn, Narrow Margin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narrow Margin Context triple: [Anne Archer, actedIn, Narrow Margin]
-
A.
Narrow Margin
chosen
Narrow Margin is a 1990 American thriller film starring Gene Hackman as a district attorney protecting a murder witness aboard a moving train.
-
B.
Close Edge
"Close Edge" is a track by rapper and actor Mos Def from his genre-blending 2004 album *The New Danger*.
-
C.
Margin for Error
"Margin for Error" is a 1939 satirical play by Clare Boothe Luce that blends comedy and political commentary around a murder mystery involving a Nazi consul in New York.
-
D.
Close to Critical
Close to Critical is a hard science fiction novel by Hal Clement that explores survival and environmental extremes on a high-gravity alien world.
-
E.
This Close
This Close is a groundbreaking dramedy television series created by and starring deaf writers/actors, exploring the lives and relationships of two deaf best friends in Los Angeles.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2f486c8190b73c15f59335cde2 |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9d7ef48190b7acebebcb9608c3 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.