Triple
T13133296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emmet Dalton |
E312018
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Emmet |
E1003625
|
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: Emmet | Statement: [Emmet Dalton, givenName, Emmet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emmet Context triple: [Emmet Dalton, givenName, Emmet]
-
A.
Emmett
Emmett is the eccentric time-traveling scientist from the Back to the Future film series, best known for inventing the DeLorean time machine.
-
B.
Emmett
chosen
Emmett is a given name of Irish origin commonly used as a masculine first name and sometimes as a surname.
-
C.
Emmett
Emmett is a hardened yet resourceful survivor in the post-apocalyptic horror film "A Quiet Place Part II," who becomes a reluctant protector and guide to the remaining Abbott family.
-
D.
Emmet Lavery
Emmet Lavery was an American playwright and screenwriter best known for his stage and film work in the mid-20th century, including adaptations of notable historical and legal figures.
-
E.
Dante Hicks
Dante Hicks is a beleaguered convenience store clerk and the central everyman protagonist of Kevin Smith’s film "Clerks."
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b3d72c8190b69ae56435a954fa |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e2930c6c8190adf17103a6cb71b9 |
completed | May 3, 2026, 5:52 a.m. |
Created at: April 9, 2026, 9:08 p.m.