Triple
T22022820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattel, Inc. |
E543883
|
entity |
| Predicate | chairman |
P377
|
FINISHED |
| Object | Ynon Kreiz |
—
|
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: Ynon Kreiz | Statement: [Mattel, Inc., chairman, Ynon Kreiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ynon Kreiz Context triple: [Mattel, Inc., chairman, Ynon Kreiz]
-
A.
Ynon Kreiz
chosen
Ynon Kreiz is an Israeli-American media executive and businessman best known for leading major entertainment companies, including serving as CEO of Mattel and previously heading Maker Studios and Endemol.
-
B.
Kehama
Kehama is the powerful and tyrannical sorcerer-rajah who serves as the central antagonist in Robert Southey’s epic poem "The Curse of Kehama."
-
C.
Yeruham
Yeruham is a small town in Israel’s Negev desert known as a gateway to nearby geological attractions and nature reserves.
-
D.
Chyhyryn
Chyhyryn is a historic Ukrainian town that served as an early political and military center of the Cossack state in the 17th century.
-
E.
Leshem
Leshem is an ancient Canaanite city in the northern Levant, later known as Laish and associated with the biblical tribe of Dan.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c8ac6881909a9e96e0873a3ae2 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:23 p.m.