Triple

T15747112
Position Surface form Disambiguated ID Type / Status
Subject Doina Cornea E381747 entity
Predicate familyName P18 FINISHED
Object Cornea
Cornea is a transparent, dome-shaped tissue at the front of the eye that helps focus incoming light onto the retina.
 E1174276 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: Cornea | Statement: [Doina Cornea, familyName, Cornea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cornea
Context triple: [Doina Cornea, familyName, Cornea]
  • A. Corne
    Corne is a given name, typically used as a shortened or informal form of the Dutch name Cornelis.
  • B. Doina Cornea
    Doina Cornea was a prominent Romanian dissident and human rights activist who opposed the Ceaușescu regime and became a key moral voice during the country’s transition from communism.
  • C. Ornea
    Ornea is a minor figure in Greek mythology known primarily as one of the many children of the river god Asopus.
  • D. Eye
    Eye is a small historic market town in Suffolk, England, known for its medieval architecture and rural surroundings.
  • E. CLSCL
    CLSCL is the UN/LOCODE identifier for the port and transport location of Santiago, Chile.
  • 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: Cornea
Triple: [Doina Cornea, familyName, Cornea]
Generated description
Cornea is a transparent, dome-shaped tissue at the front of the eye that helps focus incoming light onto the retina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cornea
Target entity description: Cornea is a transparent, dome-shaped tissue at the front of the eye that helps focus incoming light onto the retina.
  • A. Corne
    Corne is a given name, typically used as a shortened or informal form of the Dutch name Cornelis.
  • B. Doina Cornea
    Doina Cornea was a prominent Romanian dissident and human rights activist who opposed the Ceaușescu regime and became a key moral voice during the country’s transition from communism.
  • C. Ornea
    Ornea is a minor figure in Greek mythology known primarily as one of the many children of the river god Asopus.
  • D. Eye
    Eye is a small historic market town in Suffolk, England, known for its medieval architecture and rural surroundings.
  • E. CLSCL
    CLSCL is the UN/LOCODE identifier for the port and transport location of Santiago, Chile.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502d72008190b4d13a6b3a12e467 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8309cba881909579ee5a62b3aa31 completed May 9, 2026, 6:55 p.m.
NEDg Description generation batch_69ff83d929a48190aea75597b864d210 completed May 9, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69ff846436e48190b711da134c9a3b81 completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.