Triple

T16582835
Position Surface form Disambiguated ID Type / Status
Subject Urticoideae E402878 entity
Predicate hasMember P10 FINISHED
Object Urtica E10149 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: Urtica | Statement: [Urticoideae, hasMember, Urtica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urtica
Context triple: [Urticoideae, hasMember, Urtica]
  • A. Urtica chosen
    Urtica is a genus of herbaceous plants best known for its stinging nettles, which have tiny hairs that can irritate the skin.
  • B. Teasle
    Teasle is the surname of Sheriff Will Teasle, a fictional law enforcement character best known as the antagonist in the novel and film "First Blood."
  • C. Agrimonia
    Agrimonia is a genus of herbaceous flowering plants in the rose family known for their small yellow flowers and traditional medicinal uses.
  • D. Schildkraut
    Schildkraut is a surname most notably associated with Austrian-American actor Joseph Schildkraut, an Academy Award winner known for his work in early 20th-century film and theater.
  • E. Rumex
    Rumex is a genus of flowering plants commonly known as docks and sorrels, many of which are widespread weeds or edible leafy herbs found in temperate regions worldwide.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35999088c8190900497f18728bd0b completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ef2d6048190954144ab848760ec completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.