Triple
T9970963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garde |
E196201
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Betty Garde |
E38548
|
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: Betty Garde | Statement: [Garde, hasNotableBearer, Betty Garde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betty Garde Context triple: [Garde, hasNotableBearer, Betty Garde]
-
A.
Betty Garde
chosen
Betty Garde was an American stage, film, and radio actress known for her versatile character roles in mid-20th-century theater and entertainment.
-
B.
Betty Reinhardt
Betty Reinhardt was a screenwriter best known for her work on the classic 1944 film noir "Laura."
-
C.
Betty de Noon
Betty de Noon was the wife of American actor and author Sterling Hayden, known primarily for her marriage to the Hollywood star.
-
D.
Betty Gabriel
Betty Gabriel is an American actress best known for her breakout role as the unsettling housekeeper Georgina in the horror film "Get Out."
-
E.
Betty Haas
Betty Haas is known as the former wife of American politician and longtime U.S. Senator Joe Lieberman.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b96b1c8190b9d3c1171346615a |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257c9f6cc81908256dc1e8d6c3fea |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:48 p.m.