Triple
T7687881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Iger |
E174166
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Amanda Iger |
E174166
|
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: Amanda Iger | Statement: [Bob Iger, hasChild, Amanda Iger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Iger Context triple: [Bob Iger, hasChild, Amanda Iger]
-
A.
Amanda Iger
chosen
Amanda Iger is one of the children of longtime Disney CEO and media executive Bob Iger.
-
B.
Max Iger
Max Iger is a member of the Iger family best known as one of the children of longtime Disney CEO Bob Iger.
-
C.
Megan Ellison
Megan Ellison is an American film producer and founder of Annapurna Pictures, known for backing acclaimed independent and auteur-driven films such as "Her," "Zero Dark Thirty," and "American Hustle."
-
D.
Michelle Sarandos
Michelle Sarandos is the wife of Netflix co-CEO and chief content officer Ted Sarandos.
-
E.
Laura Arrillaga-Andreessen
Laura Arrillaga-Andreessen is an American philanthropist, author, and Stanford University lecturer known for her work in strategic philanthropy and impact-driven giving.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7022530e481908ba8d531bb915214 |
completed | March 27, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a261019c8190b8ef53bfb611cef4 |
completed | March 29, 2026, 3:54 a.m. |
Created at: March 27, 2026, 4:02 p.m.