Triple

T13636925
Position Surface form Disambiguated ID Type / Status
Subject Random Early Detection E325872 entity
Predicate dropPolicy P111409 FINISHED
Object drops packets with probability increasing with average queue size 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: drops packets with probability increasing with average queue size | Statement: [Random Early Detection, dropPolicy, drops packets with probability increasing with average queue size]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: dropPolicy
Context triple: [Random Early Detection, dropPolicy, drops packets with probability increasing with average queue size]
  • A. stopPolicy
    Indicates that an entity terminates, cancels, or brings to an end a policy or ongoing course of action.
  • B. dropCondition
    Indicates that an entity ceases to satisfy, or is no longer subject to, a specified condition or requirement.
  • C. dropType
    Indicates the manner or category of how something is dropped, released, or caused to fall.
  • D. expirationPolicy
    Indicates the rules or conditions under which something becomes invalid, unusable, or no longer in effect after a certain time or event.
  • E. boardingPolicy
    Indicates the rules or procedures governing how and in what order passengers are allowed to board a vehicle or vessel.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc60635d08190899806fe8936f02a completed April 12, 2026, 4:19 p.m.
PD Predicate disambiguation batch_69dbbe85e1c4819095194f4b7f9f6118 completed April 12, 2026, 3:47 p.m.
PDg Predicate description generation batch_69dbc6043e148190a2a25f929cfa35e5 completed April 12, 2026, 4:19 p.m.
Created at: April 9, 2026, 9:51 p.m.