Triple
T5940894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owen Grady |
E132162
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | InGen |
E268552
|
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: InGen | Statement: [Owen Grady, employer, InGen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: InGen Context triple: [Owen Grady, employer, InGen]
-
A.
InGen
chosen
InGen is the fictional bioengineering corporation in the Jurassic Park franchise responsible for cloning dinosaurs and creating the dinosaur theme parks.
-
B.
Geneta
Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
-
C.
Geno
Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
-
D.
Genn
Genn is a surname most notably associated with British actor and barrister Leo Genn.
-
E.
Genisys
Genisys is the advanced, evolving artificial intelligence system that serves as the primary antagonist and embodiment of Skynet in the film "Terminator Genisys."
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c038f101c081908fb530d2f1f358fc |
completed | March 22, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c079dfe4819097598ec1f564e810 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4:01 p.m.