Triple

T8314769
Position Surface form Disambiguated ID Type / Status
Subject Museum Koenig E194678 entity
Predicate shortName P43 FINISHED
Object ZFMK
ZFMK is the Zoological Research Museum Alexander Koenig in Bonn, Germany, a major natural history and biodiversity research institution.
E725532 NE FINISHED

How this triple was built (4 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: ZFMK | Statement: [Museum Koenig, shortName, ZFMK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ZFMK
Context triple: [Museum Koenig, shortName, ZFMK]
  • A. FZ
    FZ is the vehicle registration code assigned to cars registered in the city of Zielona Góra in western Poland.
  • B. FZ
    FZ is the IATA airline designator assigned to flydubai, the low-cost carrier based in Dubai, United Arab Emirates.
  • C. GFKZ
    GFKZ is the radio call sign assigned to the British Royal Research Ship (RRS) Charles Darwin, an oceanographic research vessel.
  • D. ZMCK
    ZMCK is the ICAO airport code assigned to Chinggis Khaan International Airport in Mongolia.
  • E. FMCZ
    FMCZ is the ICAO airport code for Dzaoudzi–Pamandzi International Airport, the main air gateway to the French overseas department of Mayotte in the Indian Ocean.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ZFMK
Triple: [Museum Koenig, shortName, ZFMK]
Generated description
ZFMK is the Zoological Research Museum Alexander Koenig in Bonn, Germany, a major natural history and biodiversity research institution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ZFMK
Target entity description: ZFMK is the Zoological Research Museum Alexander Koenig in Bonn, Germany, a major natural history and biodiversity research institution.
  • A. FZ
    FZ is the vehicle registration code assigned to cars registered in the city of Zielona Góra in western Poland.
  • B. FZ
    FZ is the IATA airline designator assigned to flydubai, the low-cost carrier based in Dubai, United Arab Emirates.
  • C. GFKZ
    GFKZ is the radio call sign assigned to the British Royal Research Ship (RRS) Charles Darwin, an oceanographic research vessel.
  • D. ZMCK
    ZMCK is the ICAO airport code assigned to Chinggis Khaan International Airport in Mongolia.
  • E. FMCZ
    FMCZ is the ICAO airport code for Dzaoudzi–Pamandzi International Airport, the main air gateway to the French overseas department of Mayotte in the Indian Ocean.
  • F. None of above. chosen

Provenance (5 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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f52c5cc8190b5a95ee0aa4ddda5 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd9583fa8081909778288f4c96de72 completed April 1, 2026, 10 p.m.
NEDg Description generation batch_69cdab5d649c819098a7643d5a0b7827 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2c2e2248190bf52466abaebfe29 completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:55 p.m.