Triple
T35042059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resident Evil (2002 film) |
E1011094
|
entity |
| Predicate | featuresArtificialIntelligence |
P33054
|
FINISHED |
| Object | Red Queen |
E1066468
|
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: Red Queen | Statement: [Resident Evil (2002 film), featuresArtificialIntelligence, Red Queen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresArtificialIntelligence Context triple: [Resident Evil (2002 film), featuresArtificialIntelligence, Red Queen]
-
A.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
B.
intelligenceUse
Indicates the use or application of intelligence by one entity toward a task, situation, or another entity.
-
C.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
D.
featuresArtifact
chosen
Indicates that one entity prominently includes, presents, or showcases another entity as an artifact.
-
E.
featuresInfluence
Indicates that certain features or characteristics have an effect on or contribute to changes in other features, outcomes, or behaviors.
- F. None of above.
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_69f76dcea02c81908542a223f6d5059f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37bd30ecfc81908d9b14c44901d297 |
completed | June 21, 2026, 10:30 a.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.