Triple

T1707277
Position Surface form Disambiguated ID Type / Status
Subject Army Aviation Forces E36899 entity
Predicate abbreviation P43 FINISHED
Object FAMET E192338 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: FAMET | Statement: [Army Aviation Forces, abbreviation, FAMET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FAMET
Context triple: [Army Aviation Forces, abbreviation, FAMET]
  • A. FAMET chosen
    FAMET is the Spanish Army’s aviation branch responsible for operating and supporting its helicopter and air mobility units.
  • B. Faetar
    Faetar is a rare Romance language variety spoken by a small Franco-Provençal community in southern Italy, notable for preserving archaic features within an Italo-Romance environment.
  • C. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • D. Fuhse
    Fuhse is a river in Lower Saxony, Germany, that flows through several towns before joining the Aller River.
  • E. FABLife
    FABLife is a lifestyle-focused daytime talk show that featured a panel of hosts, including Chrissy Teigen, discussing topics like fashion, beauty, food, and pop culture.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62f6fc9c8190b61cc9872cc2adc0 completed March 6, 2026, 5:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0cf5a3481908434c725e85360a2 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:30 p.m.