Triple

T3853331
Position Surface form Disambiguated ID Type / Status
Subject Agly E85349 entity
Predicate flowsNear P350 FINISHED
Object Vingrau
Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
 E392499 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: Vingrau | Statement: [Agly, flowsNear, Vingrau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vingrau
Context triple: [Agly, flowsNear, Vingrau]
  • A. Vánagandr
    Vánagandr is an alternate name for Fenrir, the monstrous wolf of Norse mythology prophesied to kill Odin during Ragnarök.
  • B. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • C. Vitlycke
    Vitlycke is a renowned Bronze Age rock carving site in Tanum, Sweden, noted for its extensive petroglyphs and archaeological significance.
  • D. Vimioso
    Vimioso is a municipality in northeastern Portugal known for its strong cultural ties to the Mirandese language and traditional rural heritage.
  • E. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • 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: Vingrau
Triple: [Agly, flowsNear, Vingrau]
Generated description
Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vingrau
Target entity description: Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
  • A. Vánagandr
    Vánagandr is an alternate name for Fenrir, the monstrous wolf of Norse mythology prophesied to kill Odin during Ragnarök.
  • B. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • C. Vitlycke
    Vitlycke is a renowned Bronze Age rock carving site in Tanum, Sweden, noted for its extensive petroglyphs and archaeological significance.
  • D. Vimioso
    Vimioso is a municipality in northeastern Portugal known for its strong cultural ties to the Mirandese language and traditional rural heritage.
  • E. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec0438308190865ff74bee5a1cf2 completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5041c7250819093b2743afeb6e36c completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b504c46dcc8190a9775c39e5c734a9 completed March 14, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_69b505742830819093a861bde17c03c0 completed March 14, 2026, 6:51 a.m.
Created at: March 9, 2026, 3:19 p.m.