Triple
T22355697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara Worthington |
E552646
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Worthington |
—
|
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: Worthington | Statement: [Lara Worthington, familyName, Worthington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Worthington Context triple: [Lara Worthington, familyName, Worthington]
-
A.
Worthington
chosen
Worthington is an English-origin surname borne by numerous notable figures in politics, industry, and the arts.
-
B.
Worthington
Worthington is a small village and civil parish in the North West Leicestershire district of Leicestershire, England.
-
C.
Worthington, Ohio
Worthington, Ohio is a historic suburban city just north of Columbus known for its New England–style village green, strong schools, and community-focused character.
-
D.
Dennison
Dennison is the middle name of William Stephens, used as part of his full personal name.
-
E.
Holton
Holton is a prestigious all-girls independent college-preparatory school located in Bethesda, Maryland.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157cf94508190b0f2c63ddfecb813 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.