Triple
T4945738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Temple |
E111044
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Linda Susan Agar
Linda Susan Agar is the daughter of famed American child star and diplomat Shirley Temple.
|
E483248
|
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: Linda Susan Agar | Statement: [Shirley Temple, child, Linda Susan Agar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Susan Agar Context triple: [Shirley Temple, child, Linda Susan Agar]
-
A.
Linda Keene
Linda Keene is the wealthy and sophisticated socialite love interest of Fred Astaire’s character in the 1937 musical film "Shall We Dance."
-
B.
Denise Lakofski
Denise Lakofski, better known as Denise Scott Brown, is a pioneering architect, urban planner, and theorist whose work and writings have profoundly influenced postmodern architecture and urban design.
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Linda Banwell
Linda Banwell is best known as the wife of the late English actor and director Bob Hoskins.
-
E.
Lisa Lassek
Lisa Lassek is an American film and television editor known for her frequent collaborations with Joss Whedon on projects such as major Marvel superhero films and cult TV series.
- 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: Linda Susan Agar Triple: [Shirley Temple, child, Linda Susan Agar]
Generated description
Linda Susan Agar is the daughter of famed American child star and diplomat Shirley Temple.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Linda Susan Agar Target entity description: Linda Susan Agar is the daughter of famed American child star and diplomat Shirley Temple.
-
A.
Linda Keene
Linda Keene is the wealthy and sophisticated socialite love interest of Fred Astaire’s character in the 1937 musical film "Shall We Dance."
-
B.
Denise Lakofski
Denise Lakofski, better known as Denise Scott Brown, is a pioneering architect, urban planner, and theorist whose work and writings have profoundly influenced postmodern architecture and urban design.
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Linda Banwell
Linda Banwell is best known as the wife of the late English actor and director Bob Hoskins.
-
E.
Lisa Lassek
Lisa Lassek is an American film and television editor known for her frequent collaborations with Joss Whedon on projects such as major Marvel superhero films and cult TV series.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70aa890c81908e685ec5e88cae1f |
completed | March 20, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81cc862081908b42686f04915238 |
completed | March 21, 2026, 11:32 a.m. |
| NEDg | Description generation | batch_69be82eb7da481909f589d096b9dfa7c |
completed | March 21, 2026, 11:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be8349507481908643591de7f03f42 |
completed | March 21, 2026, 11:38 a.m. |
Created at: March 20, 2026, 1:31 p.m.