Triple

T2094744
Position Surface form Disambiguated ID Type / Status
Subject Fejér County E32753 entity
Predicate containsTown P847 FINISHED
Object Mór
Mór is a town in central Hungary known for its wine production and location between the Vértes and Bakony hills.
 E234841 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: Mór | Statement: [Fejér County, containsTown, Mór]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mór
Context triple: [Fejér County, containsTown, Mór]
  • A. Velkua
    Velkua is a former island municipality in southwestern Finland known for its coastal archipelago landscape in the Baltic Sea.
  • B. Bór
    Bór is the wartime nickname of Tadeusz Bór-Komorowski, the Polish general who commanded the Home Army and led the Warsaw Uprising during World War II.
  • C. Örtze
    Örtze is a river in Lower Saxony, Germany, known for flowing through the Lüneburg Heath before joining the Aller.
  • D. Tura
    Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
  • E. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • 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: Mór
Triple: [Fejér County, containsTown, Mór]
Generated description
Mór is a town in central Hungary known for its wine production and location between the Vértes and Bakony hills.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mór
Target entity description: Mór is a town in central Hungary known for its wine production and location between the Vértes and Bakony hills.
  • A. Velkua
    Velkua is a former island municipality in southwestern Finland known for its coastal archipelago landscape in the Baltic Sea.
  • B. Bór
    Bór is the wartime nickname of Tadeusz Bór-Komorowski, the Polish general who commanded the Home Army and led the Warsaw Uprising during World War II.
  • C. Örtze
    Örtze is a river in Lower Saxony, Germany, known for flowing through the Lüneburg Heath before joining the Aller.
  • D. Tura
    Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
  • E. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba99ddc48190bb2097b56efb7aca completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae305cb77c819085c4f3eb2223f749 completed March 9, 2026, 2:28 a.m.
NEDg Description generation batch_69ae30f6b7c4819080cb7cb7adc1f6d3 completed March 9, 2026, 2:31 a.m.
NED2 Entity disambiguation (via description) batch_69ae31871d408190a4ae64372660fa79 completed March 9, 2026, 2:33 a.m.
Created at: March 4, 2026, 7:43 p.m.