Triple
T18102230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward John Trelawny |
E433250
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trelawny |
—
|
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: Trelawny | Statement: [Edward John Trelawny, familyName, Trelawny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trelawny Context triple: [Edward John Trelawny, familyName, Trelawny]
-
A.
Trelawney
Trelawney is a small town in Zimbabwe’s Mashonaland West Province, known primarily for its agricultural activities, especially tobacco farming.
-
B.
Trelawney
chosen
Trelawney is the surname of Sybill Trelawney, the eccentric Divination professor and seer in the Harry Potter series.
-
C.
Grindleton
Grindleton is a small rural village in Lancashire, England, situated near the River Ribble and known for its scenic countryside setting.
-
D.
Skerrit
Skerrit is the surname of Roosevelt Skerrit, the long-serving Prime Minister of Dominica.
-
E.
Sarakiniko
Sarakiniko is a strikingly unique beach on the Greek island of Milos, famous for its smooth white volcanic rock formations that resemble a lunar landscape.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb6fed8819090798683353a5c08 |
completed | April 19, 2026, 1:50 p.m. |
Created at: April 10, 2026, 10:28 a.m.