Triple
T12860285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester Hanks |
E307566
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Elizabeth Hanks |
E196040
|
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: Elizabeth Hanks | Statement: [Chester Hanks, hasRelative, Elizabeth Hanks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Hanks Context triple: [Chester Hanks, hasRelative, Elizabeth Hanks]
-
A.
Elizabeth Hanks
chosen
Elizabeth Hanks is an American actress and writer, known for her supporting roles in films like "Forrest Gump" and for being the daughter of actor Tom Hanks.
-
B.
Mary Harkness
Mary Harkness was the first wife of American industrialist and railroad magnate Henry Flagler, with whom she shared the early years of his rise in the oil and transportation industries.
-
C.
Mary Haines
Mary Haines is the gracious, upper-class New York wife and mother whose marital troubles and friendships drive the plot of the 1939 film "The Women."
-
D.
Sarah Haskins
Sarah Haskins is an American comedian and writer known for her sharp feminist satire and work on projects like the film "Trophy Wife."
-
E.
Mary Hanson
Mary Hanson was the mother of Harlem Renaissance novelist Nella Larsen and part of the family background that shaped Larsen’s life and work.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708ba74881909b16c1e2ef5115db |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f72e950819082326a8f84a8a260 |
completed | May 3, 2026, 5:01 p.m. |
Created at: April 9, 2026, 5:37 p.m.