Triple

T14937032
Position Surface form Disambiguated ID Type / Status
Subject USMOB E372420 entity
Predicate notation P6184 FINISHED
Object USMOB E372420 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: USMOB | Statement: [USMOB, notation, USMOB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: USMOB
Context triple: [USMOB, notation, USMOB]
  • A. USMOB chosen
    USMOB is the UN/LOCODE identifier for the Port of Mobile, a major deep-water seaport located in Mobile, Alabama, USA.
  • B. A.U.S.A.
    A.U.S.A. is a short-lived early-2000s NBC legal sitcom starring Scott Foley as an idealistic young federal prosecutor navigating quirky cases and office politics.
  • C. Watergang
    Watergang is a small village in the Dutch province of North Holland, known for its traditional polder landscape and characteristic waterways.
  • D. Omnibus
    Omnibus is a celebrated painting by Swedish artist Anders Zorn, known for its dynamic depiction of urban life and masterful handling of light and atmosphere.
  • E. The Bureau
    The Bureau is a French television crime drama series starring Gilbert Melki as a member of France’s external intelligence agency, acclaimed for its realistic portrayal of espionage.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64904d88190b6b4140da8e8199d completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e8e9c0c81909cfb1e02987527c0 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 2:37 a.m.