Triple
T20124551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finian Paul Greenall |
E490712
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Greenall |
—
|
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: Greenall | Statement: [Finian Paul Greenall, hasFamilyName, Greenall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greenall Context triple: [Finian Paul Greenall, hasFamilyName, Greenall]
-
A.
Greenall
chosen
Greenall is an English surname, historically associated with families involved in brewing and regional business in the United Kingdom.
-
B.
Tyzack
Tyzack is an English surname most notably associated with acclaimed stage and screen actress Margaret Tyzack.
-
C.
Guyer
Guyer is a surname of German origin borne by various individuals, including athletes, academics, and public figures.
-
D.
Greenhalge
Greenhalge is an English-origin surname most notably associated with Frederic T. Greenhalge, a 19th-century governor of Massachusetts.
-
E.
White Galloway
White Galloway is a rare, naturally polled, white-coated variant of the hardy Galloway beef cattle breed, valued for its adaptability to harsh climates and quality meat.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667412b888190b43f7dd1ccdbad01 |
completed | April 20, 2026, 5:49 p.m. |
Created at: April 11, 2026, 11:30 p.m.