Triple

T16284240
Position Surface form Disambiguated ID Type / Status
Subject Lashana Lynch E395347 entity
Predicate givenName P17 FINISHED
Object Lashana
Lashana is the first name of British actress Lashana Lynch, known for her roles in films such as "Captain Marvel" and the James Bond movie "No Time to Die."
 E1204470 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: Lashana | Statement: [Lashana Lynch, givenName, Lashana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lashana
Context triple: [Lashana Lynch, givenName, Lashana]
  • A. Lana
    Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
  • B. Lana
    Lana is a filmmaker best known as one of the Wachowski sisters, the co-creators of The Matrix film series.
  • C. Lana
    Lana is a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
  • D. Lana
    Lana is a professional wrestler and television personality best known for her time in WWE, where she appeared prominently as a manager and in-ring performer.
  • E. Lana
    Lana is the given name of actress Lana Condor, best known for starring in the "To All the Boys I've Loved Before" film series.
  • 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: Lashana
Triple: [Lashana Lynch, givenName, Lashana]
Generated description
Lashana is the first name of British actress Lashana Lynch, known for her roles in films such as "Captain Marvel" and the James Bond movie "No Time to Die."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lashana
Target entity description: Lashana is the first name of British actress Lashana Lynch, known for her roles in films such as "Captain Marvel" and the James Bond movie "No Time to Die."
  • A. Lana
    Lana is a filmmaker best known as one of the Wachowski sisters, the co-creators of The Matrix film series.
  • B. Lana
    Lana is the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
  • C. Lana
    Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
  • D. Lana
    Lana is a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
  • E. Lana
    Lana is a professional wrestler and television personality best known for her time in WWE, where she appeared prominently as a manager and in-ring performer.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24912c5808190a0d9c9f491315068 completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c8f51c8190b73cdf2834eda57f completed May 10, 2026, 5:29 a.m.
NEDg Description generation batch_6a0019c847a0819081b92e21ced73824 completed May 10, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a001a7dcf888190b66122f2bfc7388b completed May 10, 2026, 5:41 a.m.
Created at: April 10, 2026, 5:05 a.m.