Triple
T22022793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattel, Inc. |
E543883
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
American Girl
American Girl is a popular line of historical and contemporary dolls and related books and accessories that focus on the diverse stories and experiences of girls in America.
|
E109030
|
NE FINISHED |
How this triple was built (4 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: American Girl | Statement: [Mattel, Inc., brand, American Girl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: American Girl Context triple: [Mattel, Inc., brand, American Girl]
-
A.
Anais
Anais is a fictional pink rabbit character from the animated television series "The Amazing World of Gumball," known as Gumball’s highly intelligent younger sister.
-
B.
Anna-Lou
Anna-Lou is the birth name of renowned American portrait photographer Annie Leibovitz, famous for her iconic celebrity and editorial images.
-
C.
Annalee
"Annalee" is a song featured on the album "Something Worth Saving" by American singer-songwriter Gavin DeGraw.
-
D.
Nadine
Nadine is a feminine given name used in various cultures, often associated with the meaning "hope."
-
E.
Nadine
"Nadine" is a classic 1964 rock and roll song by Chuck Berry, known for its vivid storytelling and driving guitar riff.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: American Girl Triple: [Mattel, Inc., brand, American Girl]
Generated description
American Girl is a popular line of historical and contemporary dolls and related books and accessories that focus on the diverse stories and experiences of girls in America.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: American Girl Target entity description: American Girl is a popular line of historical and contemporary dolls and related books and accessories that focus on the diverse stories and experiences of girls in America.
-
A.
American Girl
chosen
"American Girl" is a classic rock song by Tom Petty and the Heartbreakers, known for its jangly guitars, driving rhythm, and enduring popularity since its 1976 release.
-
B.
Anais
Anais is a fictional pink rabbit character from the animated television series "The Amazing World of Gumball," known as Gumball’s highly intelligent younger sister.
-
C.
Anna-Lou
Anna-Lou is the birth name of renowned American portrait photographer Annie Leibovitz, famous for her iconic celebrity and editorial images.
-
D.
Annalee
"Annalee" is a song featured on the album "Something Worth Saving" by American singer-songwriter Gavin DeGraw.
-
E.
Nadine
"Nadine" is a classic 1964 rock and roll song by Chuck Berry, known for its vivid storytelling and driving guitar riff.
- F. None of above.
Provenance (5 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c8ac6881909a9e96e0873a3ae2 |
completed | April 28, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a738527b481908b8f5aeb7d4cf5c7 |
completed | May 18, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_6a0a745e534881909a681b9f2234afa5 |
completed | May 18, 2026, 2:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a7857e6dc819088b592cdff7d4cf3 |
completed | May 18, 2026, 2:24 a.m. |
Created at: April 16, 2026, 8:23 p.m.