Triple

T13317489
Position Surface form Disambiguated ID Type / Status
Subject Data Archiving and Networked Services E317225 entity
Predicate shortName P43 FINISHED
Object DANS
DANS is a Dutch national institute that preserves and provides access to research data in the social sciences and humanities.
 E1033559 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: DANS | Statement: [Data Archiving and Networked Services, shortName, DANS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DANS
Context triple: [Data Archiving and Networked Services, shortName, DANS]
  • A. Dranse
    The Dranse is a river in the Haute-Savoie region of France that flows from the Alps into Lake Geneva near Thonon-les-Bains.
  • B. Dancina
    Dancina is a song by the artist Empress, known for its catchy, danceable pop sound.
  • C. Tanca
    Tanca was a historical figure known primarily as the assassin of King Jayanegara of the Majapahit Kingdom in 14th-century Java.
  • D. La Danse (celebration of movement)
    La Danse (celebration of movement) is a dynamic 19th-century sculptural group by Jean-Baptiste Carpeaux that exuberantly depicts intertwined, dancing figures in a vivid expression of joy and motion.
  • E. The Dance
    "The Dance" is a painting by French Rococo artist Antoine Watteau, exemplifying his elegant, theatrical scenes of aristocratic leisure and refined movement.
  • 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: DANS
Triple: [Data Archiving and Networked Services, shortName, DANS]
Generated description
DANS is a Dutch national institute that preserves and provides access to research data in the social sciences and humanities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DANS
Target entity description: DANS is a Dutch national institute that preserves and provides access to research data in the social sciences and humanities.
  • A. Dranse
    The Dranse is a river in the Haute-Savoie region of France that flows from the Alps into Lake Geneva near Thonon-les-Bains.
  • B. Dancina
    Dancina is a song by the artist Empress, known for its catchy, danceable pop sound.
  • C. Tanca
    Tanca was a historical figure known primarily as the assassin of King Jayanegara of the Majapahit Kingdom in 14th-century Java.
  • D. La Danse (celebration of movement)
    La Danse (celebration of movement) is a dynamic 19th-century sculptural group by Jean-Baptiste Carpeaux that exuberantly depicts intertwined, dancing figures in a vivid expression of joy and motion.
  • E. The Dance
    "The Dance" is a painting by French Rococo artist Antoine Watteau, exemplifying his elegant, theatrical scenes of aristocratic leisure and refined movement.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f9a384819085890e18255ee339 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716ee695c81909ffeeb0901ee66c1 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f717f4d80c8190a1a95c0f2c83c563 completed May 3, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_69f718b852808190a2a0fb48424bffb0 completed May 3, 2026, 9:43 a.m.
Created at: April 9, 2026, 9:29 p.m.