Triple
T10173032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenella Fielding |
E235778
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
Tessa Feldman
Tessa Feldman is the mother of renowned British actress Fenella Fielding.
|
E868862
|
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: Tessa Feldman | Statement: [Fenella Fielding, mother, Tessa Feldman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Feldman Context triple: [Fenella Fielding, mother, Tessa Feldman]
-
A.
Rebecca Feldman
Rebecca Feldman is a theater artist best known for creating the original improvisational concept that evolved into the Tony Award–winning musical "The 25th Annual Putnam County Spelling Bee."
-
B.
Larissa Howard
Larissa Howard is known as the daughter of British military historian and politician Michael Howard.
-
C.
Tessa Ross
Tessa Ross is a prominent British film and television producer known for backing acclaimed, often auteur-driven projects across UK cinema and high-end TV drama.
-
D.
Tana Mundkowsky
Tana Mundkowsky is an American woman best known as the wife of The Killers’ lead singer Brandon Flowers and for her influence on some of the band’s songs and imagery.
-
E.
Emily Dreyfuss
Emily Dreyfuss is an American journalist and writer known for her work on technology, politics, and digital culture for outlets such as WIRED and the Harvard Shorenstein Center.
- 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: Tessa Feldman Triple: [Fenella Fielding, mother, Tessa Feldman]
Generated description
Tessa Feldman is the mother of renowned British actress Fenella Fielding.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tessa Feldman Target entity description: Tessa Feldman is the mother of renowned British actress Fenella Fielding.
-
A.
Rebecca Feldman
Rebecca Feldman is a theater artist best known for creating the original improvisational concept that evolved into the Tony Award–winning musical "The 25th Annual Putnam County Spelling Bee."
-
B.
Larissa Howard
Larissa Howard is known as the daughter of British military historian and politician Michael Howard.
-
C.
Tessa Ross
Tessa Ross is a prominent British film and television producer known for backing acclaimed, often auteur-driven projects across UK cinema and high-end TV drama.
-
D.
Tana Mundkowsky
Tana Mundkowsky is an American woman best known as the wife of The Killers’ lead singer Brandon Flowers and for her influence on some of the band’s songs and imagery.
-
E.
Emily Dreyfuss
Emily Dreyfuss is an American journalist and writer known for her work on technology, politics, and digital culture for outlets such as WIRED and the Harvard Shorenstein Center.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9f6dd8819081588600499165ee |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d54c32c8190b175a30c7c905cd2 |
completed | April 10, 2026, 2:46 p.m. |
| NEDg | Description generation | batch_69d9107c75108190994939ab46aa642f |
completed | April 10, 2026, 3 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9154c922c81909991f87f89c083cd |
completed | April 10, 2026, 3:20 p.m. |
Created at: March 30, 2026, 9:10 p.m.