Triple
T15330253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stinky Pete the Prospector |
E366513
|
entity |
| Predicate | roleInToyStory2 |
P118141
|
FINISHED |
| Object | main antagonist |
—
|
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: main antagonist | Statement: [Stinky Pete the Prospector, roleInToyStory2, main antagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInToyStory2 Context triple: [Stinky Pete the Prospector, roleInToyStory2, main antagonist]
-
A.
roleInShrek2
Indicates that an entity has a specific acting or character role in the movie "Shrek 2".
-
B.
roleInShrekForeverAfter
Indicates that an entity has a specific acting or production role in the movie "Shrek Forever After."
-
C.
roleInShrekTheThird
Indicates that an entity has a specific role or part in the movie "Shrek the Third."
-
D.
roleInTangled
Indicates that an entity has a specific role or function within the context of "Tangled" (e.g., the film, story, or related production).
-
E.
roleInDonkeyKongCountry
Indicates the specific role or function an entity has within the context of Donkey Kong Country.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:17 a.m.