Triple
T13773936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iron Will |
E330951
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Mackenzie Astin |
E563199
|
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: Mackenzie Astin | Statement: [Iron Will, hasCastMember, Mackenzie Astin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mackenzie Astin Context triple: [Iron Will, hasCastMember, Mackenzie Astin]
-
A.
Mackenzie Astin
chosen
Mackenzie Astin is an American actor known for his roles in film and television, including the TV series "The Facts of Life."
-
B.
Mackenzie Foy
Mackenzie Foy is an American actress and model best known for her role as Renesmee Cullen in the Twilight film series and for starring in films such as Interstellar and The Nutcracker and the Four Realms.
-
C.
Josh Hutcherson
Josh Hutcherson is an American actor best known for his role as Peeta Mellark in "The Hunger Games" film series.
-
D.
Logan Lerman
Logan Lerman is an American actor best known for his lead role in the "Percy Jackson" film series and performances in movies such as "The Perks of Being a Wallflower" and "Fury."
-
E.
Asa Butterfield
Asa Butterfield is an English actor known for his leading roles in films like "Hugo" and the series "Sex Education."
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de023774b48190b19e43e87b94ba77 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07460c081908b3836a3ec382961 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:10 p.m.