Triple
T7137696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toy Town |
E166349
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object | Dinah Doll |
E166355
|
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: Dinah Doll | Statement: [Toy Town, notableCharacter, Dinah Doll]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dinah Doll Context triple: [Toy Town, notableCharacter, Dinah Doll]
-
A.
Dinah Doll
chosen
Dinah Doll is a character from the children's franchise "Noddy," known as one of Noddy's close friends in Toyland.
-
B.
Doll Conovan
Doll Conovan is a central female character in the 1950 film noir "The Asphalt Jungle," known for her loyalty and emotional depth amid the story’s criminal underworld.
-
C.
Babydoll
"Babydoll" is a song by the American alternative rock band Butterfly.
-
D.
Dora
Dora is the given name of Dora Sigerson Shorter, an Irish poet associated with the late 19th- and early 20th-century literary revival.
-
E.
Dora
Dora is a character in Jim Jarmusch’s film "Broken Flowers," known as one of Don Johnston’s former girlfriends whom he visits while searching for the mother of his alleged son.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e6939b788190929e92ff481f2ee4 |
completed | March 27, 2026, 8:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a34b99048190a8e77cd0fe253611 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:45 p.m.