Triple
T1813572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amelia Lee Jackson |
E40383
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Amelia |
E134547
|
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: Amelia | Statement: [Amelia Lee Jackson, givenName, Amelia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amelia Context triple: [Amelia Lee Jackson, givenName, Amelia]
-
A.
Amelia
chosen
Amelia was a British princess of the early 18th century, the daughter of King George II and Queen Caroline of Ansbach.
-
B.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
-
C.
Jean Batten
Jean Batten was a pioneering New Zealand aviator famed for her record-breaking solo long-distance flights in the 1930s.
-
D.
Henrietta
Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
-
E.
Louise
Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c905ec8190bea7cd72d218487a |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5e5142c8190bc90da38b02e95e2 |
completed | March 8, 2026, 5:46 p.m. |
Created at: March 4, 2026, 7:32 p.m.