Triple
T4765766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winona Ryder |
E105806
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ryder |
E345598
|
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: Ryder | Statement: [Winona Ryder, familyName, Ryder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryder Context triple: [Winona Ryder, familyName, Ryder]
-
A.
Ryder
chosen
Ryder is a modernist novel by Djuna Barnes, known for its experimental style and exploration of unconventional family and sexual relationships.
-
B.
Ryder
Ryder is the young, tech-savvy leader of the PAW Patrol team who guides a group of rescue pups on missions to protect their community.
-
C.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
D.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
E.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6534d6b48190911c295b5601a762 |
completed | March 20, 2026, 3:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a8bd5248190bd6cc79170919148 |
completed | March 21, 2026, 6:28 a.m. |
Created at: March 20, 2026, 1:21 p.m.