Triple
T7407135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanna Page |
E170901
|
entity |
| Predicate | playedRole |
P3512
|
FINISHED |
| Object | Doris |
E526050
|
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: Doris | Statement: [Joanna Page, playedRole, Doris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doris Context triple: [Joanna Page, playedRole, Doris]
-
A.
Doris
Doris is an Oceanid from Greek mythology, known as the wife of the sea god Nereus and mother of the Nereids.
-
B.
Doris
Doris was the first wife of Herod the Great and the mother of his son Antipater in the Herodian royal family.
-
C.
Doris
Doris is the given name of Doris Buffett, an American philanthropist and sister of investor Warren Buffett, known for her charitable work and focus on direct, person-to-person giving.
-
D.
Gladys
Gladys is a feminine given name of English origin that was especially popular in the late 19th and early 20th centuries.
-
E.
Doris Dowling
chosen
Doris Dowling was an American film and television actress best known for her roles in classic 1940s noir and drama films.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f298f2388190afc944c9bc78749a |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8111adbf48190a04df3cec1017b39 |
completed | March 28, 2026, 5:34 p.m. |
Created at: March 27, 2026, 3:10 p.m.