Triple

T9472369
Position Surface form Disambiguated ID Type / Status
Subject Sundern E228422 entity
Predicate hasTwinTown P919 FINISHED
Object Benet
Benet is a commune in the Vendée department of western France, known for its rural character and location near the Marais Poitevin marshlands.
 E800259 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: Benet | Statement: [Sundern, hasTwinTown, Benet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Benet
Context triple: [Sundern, hasTwinTown, Benet]
  • A. Bennett
    Bennett is a common English-language surname of Anglo-Norman origin borne by numerous notable individuals across politics, arts, and sciences.
  • B. Bennett
    Bennett is the main villain and former comrade-turned-mercenary antagonist who battles Arnold Schwarzenegger’s character in the 1985 action film "Commando."
  • C. Harper
    Harper is a small community located in Raleigh County, West Virginia, in the United States.
  • D. Harper
    Harper is a central character in the young adult novel "Watch Over Me," whose experiences and relationships drive much of the story’s emotional arc.
  • E. Harper
    Harper is a major American publishing house known for releasing a wide range of influential fiction and nonfiction works.
  • 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: Benet
Triple: [Sundern, hasTwinTown, Benet]
Generated description
Benet is a commune in the Vendée department of western France, known for its rural character and location near the Marais Poitevin marshlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Benet
Target entity description: Benet is a commune in the Vendée department of western France, known for its rural character and location near the Marais Poitevin marshlands.
  • A. Bennett
    Bennett is a common English-language surname of Anglo-Norman origin borne by numerous notable individuals across politics, arts, and sciences.
  • B. Bennett
    Bennett is the main villain and former comrade-turned-mercenary antagonist who battles Arnold Schwarzenegger’s character in the 1985 action film "Commando."
  • C. Harper
    Harper is a small community located in Raleigh County, West Virginia, in the United States.
  • D. Harper
    Harper is a common English surname of Anglo-Saxon origin, historically referring to someone who played the harp.
  • E. Harper
    Harper is a major American publishing house known for releasing a wide range of influential fiction and nonfiction works.
  • 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_69ca847162c48190b079076c9595513c completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fef6f288190b2d158c829b31de9 completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122cd0728819088f6c832cd90d832 completed April 4, 2026, 2:40 p.m.
NEDg Description generation batch_69d12350baa08190b08f619391acbd75 completed April 4, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69d123af901c819098bb1401846f0daf completed April 4, 2026, 2:43 p.m.
Created at: March 30, 2026, 7:54 p.m.