Triple

T727770
Position Surface form Disambiguated ID Type / Status
Subject Curiosity rover E14763 entity
Predicate instrument P792 FINISHED
Object DAN
DAN is a neutron-detecting scientific instrument on NASA's Curiosity rover used to measure subsurface hydrogen and infer the presence of water on Mars.
 E86323 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: DAN | Statement: [Curiosity rover, instrument, DAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DAN
Context triple: [Curiosity rover, instrument, DAN]
  • A. Dan
    Dan is a biblical figure recognized as one of the twelve sons of Jacob and the traditional ancestor of the Tribe of Dan in the Hebrew Bible.
  • B. Dern
    Dern is a surname most prominently associated with American actor Bruce Dern and his family of performers.
  • C. Danny
    Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
  • D. DAK
    DAK is the abbreviation for the German Afrika Korps, the German expeditionary force that fought in North Africa during World War II under commanders such as Erwin Rommel.
  • E. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • 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: DAN
Triple: [Curiosity rover, instrument, DAN]
Generated description
DAN is a neutron-detecting scientific instrument on NASA's Curiosity rover used to measure subsurface hydrogen and infer the presence of water on Mars.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DAN
Target entity description: DAN is a neutron-detecting scientific instrument on NASA's Curiosity rover used to measure subsurface hydrogen and infer the presence of water on Mars.
  • A. Dan
    Dan is a biblical figure recognized as one of the twelve sons of Jacob and the traditional ancestor of the Tribe of Dan in the Hebrew Bible.
  • B. Dern
    Dern is a surname most prominently associated with American actor Bruce Dern and his family of performers.
  • C. Danny
    Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
  • D. DAK
    DAK is the abbreviation for the German Afrika Korps, the German expeditionary force that fought in North Africa during World War II under commanders such as Erwin Rommel.
  • E. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • 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_69a4934c753c81909b309027e48b9b3a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5c011948190b2cfccd8fe722742 completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6375e24248190b53efa0bfc29567a completed March 3, 2026, 1:20 a.m.
NEDg Description generation batch_69a63b580b3c81909fe2ba1b0aa958b6 completed March 3, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_69a63bbb8e9881909d5ab68c4a47eb5c completed March 3, 2026, 1:39 a.m.
Created at: March 1, 2026, 7:37 p.m.