Triple
T18710266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Davi |
E457486
|
entity |
| Predicate | hasActedIn |
P15620
|
FINISHED |
| Object | Profiler |
—
|
NE NERFINISHED |
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: Profiler | Statement: [Robert Davi, hasActedIn, Profiler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Profiler Context triple: [Robert Davi, hasActedIn, Profiler]
-
A.
Profiler
Profiler is a performance analysis tool in Android development used to monitor and optimize an app’s CPU, memory, network, and energy usage in real time.
-
B.
Profiler
chosen
Profiler is an American crime drama television series centered on a forensic psychologist who uses her profiling skills to help law enforcement track down serial killers and other dangerous criminals.
-
C.
perf (Linux profiler)
perf (Linux profiler) is a powerful Linux profiling and performance analysis tool that leverages kernel performance counters to measure and diagnose system and application behavior.
-
D.
Performance Tracker
Performance Tracker is an annual analysis by the Institute for Government that assesses how effectively UK public services are performing and being managed.
-
E.
gprof
gprof is a performance analysis tool that profiles program execution to help developers identify time-consuming functions and optimize their code.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671a3c8c81909466bf5d81477a37 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:50 a.m.