Triple
T14130657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazel Jenkins |
E350154
|
entity |
| Predicate | replacedBy |
P101
|
FINISHED |
| Object | Sylvia Lucas |
E525991
|
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: Sylvia Lucas | Statement: [Hazel Jenkins, replacedBy, Sylvia Lucas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvia Lucas Context triple: [Hazel Jenkins, replacedBy, Sylvia Lucas]
-
A.
Sylvia Lucas
chosen
Sylvia Lucas is a South African politician who served as Premier of the Northern Cape province.
-
B.
Barbara Lucas
Barbara Lucas is best known as the former wife of legendary Baseball Hall of Famer Hank Aaron.
-
C.
Diane Lucas
Diane Lucas is a fictional character appearing in the Doctor Who serial "The Silence."
-
D.
Sylvia Fowler
Sylvia Fowler is a scheming, sharp-tongued Manhattan socialite and chief instigator of gossip in the classic 1939 film "The Women."
-
E.
Margaret Lucas
Margaret Lucas was the birth name of Margaret Cavendish, Duchess of Newcastle-upon-Tyne, a 17th-century English writer, philosopher, and early female scientist known for her pioneering works in natural philosophy and literature.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610aa434819096671c5aabb9134a |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff288ba908190a36c4784331d1e60 |
completed | May 10, 2026, 2:50 a.m. |
Created at: April 9, 2026, 10:47 p.m.