Triple
T5756771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Profumo affair |
E126986
|
entity |
| Predicate | involves |
P1256
|
FINISHED |
| Object |
Mandy Rice-Davies
Mandy Rice-Davies was a British model and showgirl who became a central and famously witty figure in the 1960s Profumo affair political scandal.
|
E545747
|
NE FINISHED |
How this triple was built (4 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: Mandy Rice-Davies | Statement: [Profumo affair, involves, Mandy Rice-Davies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mandy Rice-Davies Context triple: [Profumo affair, involves, Mandy Rice-Davies]
-
A.
Renée Asherson
Renée Asherson was a British stage and film actress known for her delicate, expressive performances in mid-20th-century British cinema and theatre.
-
B.
Catherine Durkan
Catherine Durkan is a notable individual associated with the Durkan family name, recognized as a bearer of this surname.
-
C.
Katy Manning
Katy Manning is a British actress best known to Doctor Who fans for playing the Third Doctor’s companion Jo Grant in the early 1970s.
-
D.
Susan Mara
Susan Mara is a member of the Mara family, the longtime owners of the NFL’s New York Giants franchise.
-
E.
Joan Sims
Joan Sims was a prolific English comedy actress best known for her roles in the "Carry On" film series and numerous British television and stage productions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mandy Rice-Davies Triple: [Profumo affair, involves, Mandy Rice-Davies]
Generated description
Mandy Rice-Davies was a British model and showgirl who became a central and famously witty figure in the 1960s Profumo affair political scandal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mandy Rice-Davies Target entity description: Mandy Rice-Davies was a British model and showgirl who became a central and famously witty figure in the 1960s Profumo affair political scandal.
-
A.
Renée Asherson
Renée Asherson was a British stage and film actress known for her delicate, expressive performances in mid-20th-century British cinema and theatre.
-
B.
Catherine Durkan
Catherine Durkan is a notable individual associated with the Durkan family name, recognized as a bearer of this surname.
-
C.
Katy Manning
Katy Manning is a British actress best known to Doctor Who fans for playing the Third Doctor’s companion Jo Grant in the early 1970s.
-
D.
Susan Mara
Susan Mara is a member of the Mara family, the longtime owners of the NFL’s New York Giants franchise.
-
E.
Joan Sims
Joan Sims was a prolific English comedy actress best known for her roles in the "Carry On" film series and numerous British television and stage productions.
- F. None of above. chosen
Provenance (5 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_69c00833a3fc81908f4bc29ed011b7a6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029084e108190988f1b5f38254007 |
completed | March 22, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e47c1788190b5883df385475237 |
completed | March 22, 2026, 11:41 p.m. |
| NEDg | Description generation | batch_69c08e5a7950819099cd9c9bd6c7a99a |
completed | March 23, 2026, 12:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08ed0c3ac8190a7093667bcd4fb0f |
completed | March 23, 2026, 12:52 a.m. |
Created at: March 22, 2026, 3:49 p.m.