Triple
T11253575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Trelawny |
E266381
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trelawny |
E115223
|
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: Trelawny | Statement: [Jonathan Trelawny, familyName, Trelawny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trelawny Context triple: [Jonathan 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.
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.
-
E.
Bayaguana
Bayaguana is a historic town and municipality in the Monte Plata province of the Dominican Republic, known for its religious traditions and rural agricultural character.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e933648481909873094bc89ed041 |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cc941d34819099ae30713bdd03e5 |
completed | April 19, 2026, 12:37 p.m. |
Created at: April 8, 2026, 9:31 p.m.