Triple
T21502855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Engelman |
E530522
|
entity |
| Predicate | roleInScoobyDoo2MonstersUnleashed |
P144643
|
FINISHED |
| Object | producer |
—
|
LITERAL 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: producer | Statement: [Robert Engelman, roleInScoobyDoo2MonstersUnleashed, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInScoobyDoo2MonstersUnleashed Context triple: [Robert Engelman, roleInScoobyDoo2MonstersUnleashed, producer]
-
A.
roleInDespicableMe2
Indicates that an entity has a specific role or participation in the movie "Despicable Me 2."
-
B.
roleInShrek2
Indicates that an entity has a specific acting or character role in the movie "Shrek 2".
-
C.
roleInMonstersInc
Indicates the specific function, position, or part an entity has within the context of the movie “Monsters, Inc.”
-
D.
roleInShrekForeverAfter
Indicates that an entity has a specific acting or production role in the movie "Shrek Forever After."
-
E.
roleInMonstersUniversity
Indicates the specific role or capacity an entity has within the context of the film "Monsters University" (e.g., character, crew position, or other involvement).
- F. None of above. chosen
Provenance (4 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea5deb388190a89a1f94285b7e55 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:24 p.m.