Triple
T9161136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Bartlett |
E219823
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | HBO Max |
E182551
|
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: HBO Max | Statement: [Murray Bartlett, employer, HBO Max]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HBO Max Context triple: [Murray Bartlett, employer, HBO Max]
-
A.
HBO Max
chosen
HBO Max is a streaming service from WarnerMedia that offers a wide library of movies, series, and original content from HBO and related brands.
-
B.
Paramount+
Paramount+ is a subscription-based streaming service from Paramount Global that offers live sports, original series, and a wide range of on-demand TV shows and movies.
-
C.
Hulu
Hulu is a U.S.-based subscription streaming service offering on-demand access to a wide range of television shows, films, and original content.
-
D.
Disney+
Disney+ is a subscription-based streaming service from The Walt Disney Company that offers movies and TV shows from Disney, Pixar, Marvel, Star Wars, National Geographic, and more.
-
E.
Netflix
Netflix is a global streaming entertainment company best known for its vast library of films and TV series and its influential original content.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ac0508190b2f5c801c2c26d66 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d07768fcd48190b7d4181e57f49753 |
completed | April 4, 2026, 2:28 a.m. |
Created at: March 30, 2026, 7:21 p.m.