Triple
T3558100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horrible Bosses 2 |
E75269
|
entity |
| Predicate | basedOnCharactersBy |
P15277
|
FINISHED |
| Object | Michael Markowitz |
E191306
|
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: Michael Markowitz | Statement: [Horrible Bosses 2, basedOnCharactersBy, Michael Markowitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Markowitz Context triple: [Horrible Bosses 2, basedOnCharactersBy, Michael Markowitz]
-
A.
Michael Markowitz
chosen
Michael Markowitz is an American comedy writer best known for co-writing the hit film "Horrible Bosses."
-
B.
Stuart Markowitz
Stuart Markowitz is a central attorney character on the television legal drama "L.A. Law," known for his earnest demeanor and complex personal and professional relationships.
-
C.
Robert Markowitz
Robert Markowitz is an American film and television director known for his work on numerous made-for-TV movies and miniseries.
-
D.
Max Handelman
Max Handelman is an American sportswriter, film producer, and co-founder of the production company Brownstone Productions.
-
E.
Michael Kagan
Michael Kagan is an Israeli technologist and entrepreneur best known as the co-founder and longtime chief technology officer of high-performance networking company Mellanox Technologies.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc086e6688190b90ae356e18b953e |
completed | March 8, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5335e1e348190912455cd90009558 |
completed | March 14, 2026, 10:07 a.m. |
Created at: March 8, 2026, 3:20 p.m.