Triple

T2685109
Position Surface form Disambiguated ID Type / Status
Subject Gerard Moerdijk E57466 entity
Predicate familyName P18 FINISHED
Object Moerdijk E360196 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: Moerdijk | Statement: [Gerard Moerdijk, familyName, Moerdijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moerdijk
Context triple: [Gerard Moerdijk, familyName, Moerdijk]
  • A. Moerdijk chosen
    Moerdijk is a municipality and industrial port area in the southern Netherlands, known for its large logistics and chemical industry complexes.
  • B. Groningen
    Groningen is a historic province in the northern Netherlands, known for its university city of the same name, flat landscapes, and rich maritime and agricultural heritage.
  • C. Zwolle
    Zwolle is a historic Dutch city in the eastern Netherlands known for its medieval center, cultural heritage, and regional economic importance.
  • D. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • E. Haarlem
    Haarlem is a historic Dutch city in the province of North Holland, known for its medieval architecture, cultural heritage, and role as a regional center near Amsterdam.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9edba5c8190b86d6cba0f1964e2 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69b37383fbf881909361d448de3c266b completed March 13, 2026, 2:16 a.m.
Created at: March 6, 2026, 9:54 p.m.