Triple
T4765765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winona Ryder |
E105806
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Winona |
E74024
|
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: Winona | Statement: [Winona Ryder, givenName, Winona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winona Context triple: [Winona Ryder, givenName, Winona]
-
A.
Winona
chosen
Winona is a historic river city in southeastern Minnesota known for its Mississippi River bluffs, cultural festivals, and regional educational institutions.
-
B.
Verna
Verna is a feminine given name that gained particular recognition through film editor Verna Fields, known for her work on movies like "Jaws."
-
C.
Alva
Alva is a small city in northwestern Oklahoma known as the county seat of Woods County and home to Northwestern Oklahoma State University.
-
D.
Alva
Alva is a small town in central Scotland situated at the foot of the Ochil Hills in Clackmannanshire.
-
E.
Alva
Alva is the middle name of the famed American inventor Thomas Edison, often used as part of his full name, Thomas Alva Edison.
- 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.