Triple

T14538426
Position Surface form Disambiguated ID Type / Status
Subject G1 GC E341109 entity
Predicate comparedWith P278 FINISHED
Object Parallel GC E341108 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: Parallel GC | Statement: [G1 GC, comparedWith, Parallel GC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parallel GC
Context triple: [G1 GC, comparedWith, Parallel GC]
  • A. Parallel GC chosen
    Parallel GC is a throughput-oriented garbage collector in the HotSpot JVM that uses multiple threads to perform stop-the-world garbage collection, aiming to maximize application performance on multi-core systems.
  • B. Serial GC
    Serial GC is a simple, single-threaded garbage collector in the HotSpot JVM designed primarily for small applications or environments with limited CPU resources.
  • C. G1 GC
    G1 GC is a server-style garbage collector for the HotSpot JVM designed to provide predictable, low-pause-time memory management by partitioning the heap into regions and collecting them incrementally.
  • D. ZGC
    ZGC is a low-latency, scalable garbage collector for the HotSpot JVM designed to handle very large heaps with minimal pause times.
  • E. SGen (generational garbage collector)
    SGen is a generational garbage collector used by the Mono runtime to improve memory management performance and reduce pause times for managed applications.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb1bb90008190947ac0961393446d completed April 14, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a5cca788190aa8762d860c78721 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:22 a.m.