Triple
T22810672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Who |
E564662
|
entity |
| Predicate | hasRelationshipWith |
P2830
|
FINISHED |
| Object | Cindy-Lou Who |
—
|
NE NERFINISHED |
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: Cindy-Lou Who | Statement: [Donna Who, hasRelationshipWith, Cindy-Lou Who]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindy-Lou Who Context triple: [Donna Who, hasRelationshipWith, Cindy-Lou Who]
-
A.
Cindy Lou Who
chosen
Cindy Lou Who is the kind-hearted little girl from Dr. Seuss's "How the Grinch Stole Christmas!" whose innocence and compassion help transform the Grinch.
-
B.
Dorothy Vallens
Dorothy Vallens is a troubled nightclub singer at the center of the dark, surreal mystery in David Lynch's film "Blue Velvet."
-
C.
Winnie Cooper
Winnie Cooper is a central coming-of-age character in the nostalgic TV series "The Wonder Years," known as Kevin Arnold’s childhood friend and love interest.
-
D.
Winnie
Winnie is a central character from the classic American sitcom "Happy Days," known for her role in the show's nostalgic portrayal of 1950s Midwestern life.
-
E.
Winnie
Winnie is a feminine given name, often used as a diminutive of names like Winifred or Gwendolyn.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d60186881908f6cb609c536dc91 |
completed | April 29, 2026, 3:39 a.m. |
Created at: April 17, 2026, 3:32 p.m.