Triple
T6204967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugo |
E138723
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Chloë Grace Moretz |
E318177
|
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: Chloë Grace Moretz | Statement: [Hugo, starredActor, Chloë Grace Moretz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chloë Grace Moretz Context triple: [Hugo, starredActor, Chloë Grace Moretz]
-
A.
Chloë Grace Moretz
chosen
Chloë Grace Moretz is an American actress known for her versatile performances in films such as "Kick-Ass," "Let Me In," and "If I Stay."
-
B.
Abigail Breslin
Abigail Breslin is an American actress who gained prominence as a child star in films like "Little Miss Sunshine" and has continued to work in both film and television.
-
C.
Mia Kirshner
Mia Kirshner is a Canadian actress known for her dark, nuanced performances in film and television, including her notable role in the crime drama "The Black Dahlia."
-
D.
Jessica Lucas
Jessica Lucas is a Canadian actress known for her roles in film and television, including prominent appearances in projects like the monster movie "Cloverfield."
-
E.
Samara Weaving
Samara Weaving is an Australian actress known for her roles in film and television, particularly in horror-comedy and thriller projects such as "Ready or Not" and "The Babysitter."
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626d96ec8190816c00c44668177d |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d9def0481909dc252d8a0ace45e |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:20 p.m.