Triple
T9235749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman J. Israel, Esq. |
E221931
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Macro Media |
E322229
|
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: Macro Media | Statement: [Roman J. Israel, Esq., productionCompany, Macro Media]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macro Media Context triple: [Roman J. Israel, Esq., productionCompany, Macro Media]
-
A.
Macro Media
chosen
Macro Media is a film and television production company known for backing culturally resonant, character-driven projects such as the 2016 drama "Fences."
-
B.
Macromedia
Macromedia was a pioneering software company best known for creating web and multimedia tools like Flash and Dreamweaver before being acquired by Adobe.
-
C.
Adnet Media
Adnet Media is a company involved in the adult entertainment industry, recognized as the parent organization behind the XBIZ Awards.
-
D.
Nine Media Corporation
Nine Media Corporation is a Philippine media company best known for operating the CNN Philippines news and current affairs television network.
-
E.
Viacom
Viacom is a major American media conglomerate known for its extensive portfolio of television networks, film production, and entertainment brands.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf09d42488190b8ccb9c4b62fdda8 |
completed | April 1, 2026, 10:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077cc774c8190bdbdd4071c11f096 |
completed | April 4, 2026, 2:30 a.m. |
Created at: March 30, 2026, 7:29 p.m.