Triple
T16686779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lainie Kazan |
E405481
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bratz |
E1118080
|
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: Bratz | Statement: [Lainie Kazan, notableWork, Bratz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bratz Context triple: [Lainie Kazan, notableWork, Bratz]
-
A.
Bratz
chosen
Bratz is a popular fashion doll franchise and multimedia brand known for its stylized, trendsetting teenage characters and spin-off films and TV shows.
-
B.
Brat
"Brat" is a track by the British electronic music producer and DJ Insomniac.
-
C.
Brat
Brat is a 2024 studio album by English pop artist Charli XCX, noted for its abrasive electronic production and confessional, internet-age lyricism.
-
D.
Barbie
Barbie is a 2023 fantasy-comedy film directed by Greta Gerwig that reimagines the iconic Mattel doll in a satirical, self-aware story exploring gender roles, identity, and consumer culture.
-
E.
Barbieland
Barbieland is a vibrant, hyper-stylized fantasy world where various Barbies and Kens live in an idealized matriarchal society.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ea63b7081908a055036172f9683 |
completed | April 18, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a43f6a08190913ca123a2377f95 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.