Triple
T4407992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy Wasserstein |
E93780
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wendy |
E328570
|
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: Wendy | Statement: [Wendy Wasserstein, givenName, Wendy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendy Context triple: [Wendy Wasserstein, givenName, Wendy]
-
A.
Wendy
chosen
Wendy is a musician best known as the guitarist for Prince’s band The Revolution and as half of the duo Wendy & Lisa.
-
B.
Wendy
Wendy is a character portrayed by actress and model Jamie King, known from her work in film and television.
-
C.
Wendy & Lisa
Wendy & Lisa is an American musical duo best known for their work with Prince and The Revolution and their subsequent career composing and performing their own eclectic pop, rock, and soundtrack music.
-
D.
Betty
"Betty" is a renowned photorealistic painting by German artist Gerhard Richter, depicting his daughter turning away from the viewer and exemplifying his exploration of perception and representation.
-
E.
Betty
Betty is the familiar nickname of Betty Ford, the former First Lady of the United States and founder of the Betty Ford Center for substance abuse treatment.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548cb92881908a3f98466da8e0a2 |
completed | March 13, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f609f7f881909d12735f4028a108 |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:28 p.m.