Triple
T21659824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Lindsay |
E534564
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Lady Killer |
—
|
NE NERFINISHED |
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: Lady Killer | Statement: [Margaret Lindsay, notableWork, Lady Killer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lady Killer Context triple: [Margaret Lindsay, notableWork, Lady Killer]
-
A.
Lady Killer
chosen
Lady Killer is a 1933 American pre-Code crime-comedy film starring James Cagney as a small-time crook who becomes a Hollywood star.
-
B.
Ladykiller
"Ladykiller" is a moody, soulful rock song by The Horrible Crowes, the side project of The Gaslight Anthem’s Brian Fallon.
-
C.
The Lady Killer
The Lady Killer is CeeLo Green’s critically acclaimed 2010 soul and R&B album best known for the hit single "Forget You."
-
D.
Killer Women
Killer Women is an American crime drama television series that follows a tough female Texas Ranger as she investigates cases involving women accused of murder.
-
E.
The Killer
The Killer is a 1989 Hong Kong action film renowned for its stylized gunplay, emotional depth, and influential blend of heroic bloodshed and crime drama.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c06844c81909b9c91e02fa4e6e1 |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.