Triple

T19275268
Position Surface form Disambiguated ID Type / Status
Subject Count of Hiémois E482035 entity
Predicate locatedIn P40 FINISHED
Object Hiémois
Hiémois is a historic region in Normandy, France, that once formed a medieval county centered around the town of Falaise.
 E651957 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: Hiémois | Statement: [Count of Hiémois, locatedIn, Hiémois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hiémois
Context triple: [Count of Hiémois, locatedIn, Hiémois]
  • A. Fallières
    Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
  • B. Hurepoix
    Hurepoix is a historic region of northern France, southwest of Paris, known for its rural landscapes and small towns such as Dourdan.
  • C. Ermontoise
    Ermontoise is the French demonym referring to a female inhabitant or native of the town of Ermont in France.
  • D. Morieux
    Morieux is a coastal commune in the Côtes-d'Armor department of Brittany in northwestern France, known for its scenic shoreline along the English Channel.
  • E. Fremault
    Fremault is the surname of American film and television actress Anita Louise.
  • 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: Hiémois
Triple: [Count of Hiémois, locatedIn, Hiémois]
Generated description
Hiémois is a historic region in Normandy, France, that once formed a medieval county centered around the town of Falaise.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hiémois
Target entity description: Hiémois is a historic region in Normandy, France, that once formed a medieval county centered around the town of Falaise.
  • A. Fallières
    Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
  • B. Hurepoix chosen
    Hurepoix is a historic region of northern France, southwest of Paris, known for its rural landscapes and small towns such as Dourdan.
  • C. Ermontoise
    Ermontoise is the French demonym referring to a female inhabitant or native of the town of Ermont in France.
  • D. Morieux
    Morieux is a coastal commune in the Côtes-d'Armor department of Brittany in northwestern France, known for its scenic shoreline along the English Channel.
  • E. Fremault
    Fremault is the surname of American film and television actress Anita Louise.
  • F. None of above.

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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbbb2fc08190b417a6d0b7a9d6b8 completed April 20, 2026, 10:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a070e76ab148190a628c64aa5922f01 completed May 15, 2026, 12:15 p.m.
NEDg Description generation batch_6a070f1618d88190ad62c1c3896dba6e completed May 15, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a070fe766d081909453b1f8563817e8 completed May 15, 2026, 12:21 p.m.
Created at: April 10, 2026, 1:29 p.m.