Triple
T19268543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Zander Rice (Logan) |
E481853
|
entity |
| Predicate | killedBy |
P4646
|
FINISHED |
| Object | Laura Kinney |
—
|
NE NERFINISHED |
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: Laura Kinney | Statement: [Dr. Zander Rice (Logan), killedBy, Laura Kinney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Kinney Context triple: [Dr. Zander Rice (Logan), killedBy, Laura Kinney]
-
A.
Laura Kinney
chosen
Laura Kinney, also known as X-23, is a Marvel Comics mutant and clone-daughter of Wolverine who becomes a prominent member of the X-Men.
-
B.
Roxanne Kowalski
Roxanne Kowalski is the intelligent and kind-hearted female lead in the 1987 romantic comedy film "Roxanne," portrayed by Daryl Hannah opposite Steve Martin.
-
C.
Rachel Kane
Rachel Kane is a key CIA operative and mission handler in the video game Call of Duty: Black Ops III, guiding and assisting the player throughout much of the campaign.
-
D.
Beth Sully
Beth Sully is known as the wife of American screenwriter and film producer Frank Butler.
-
E.
Jennifer Kale
Jennifer Kale is a powerful Marvel Comics sorceress often associated with occult storylines and supernatural teams like the Midnight Sons.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb68d0c819083ba0ce680dd7d99 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.