Triple

T11221371
Position Surface form Disambiguated ID Type / Status
Subject Alaqua Cox E265573 entity
Predicate givenName P17 FINISHED
Object Alaqua
Alaqua is a feminine given name most notably borne by American actress Alaqua Cox, known for her role in the Marvel Cinematic Universe.
 E911431 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: Alaqua | Statement: [Alaqua Cox, givenName, Alaqua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alaqua
Context triple: [Alaqua Cox, givenName, Alaqua]
  • A. Anala
    Anala is a lesser-known name or aspect of Agni, the Vedic god of fire in Hindu mythology.
  • B. Adara
    Adara is a small coastal village on Atauro Island in East Timor, known for its traditional fishing community and nearby coral reefs popular with divers and snorkelers.
  • C. Zeleia
    Zeleia was an ancient city in the region of Mysia in northwestern Asia Minor, known from classical Greek and Roman historical and geographical sources.
  • D. Sylvana
    Sylvana is a feminine given name, often considered a variant of Silvana, typically associated with meanings related to forests or woodland.
  • E. Alithea
    Alithea is a virtuous and intelligent gentlewoman in William Wycherley’s Restoration comedy "The Country Wife," whose moral integrity contrasts with the play’s surrounding hypocrisy and sexual intrigue.
  • 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: Alaqua
Triple: [Alaqua Cox, givenName, Alaqua]
Generated description
Alaqua is a feminine given name most notably borne by American actress Alaqua Cox, known for her role in the Marvel Cinematic Universe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alaqua
Target entity description: Alaqua is a feminine given name most notably borne by American actress Alaqua Cox, known for her role in the Marvel Cinematic Universe.
  • A. Anala
    Anala is a lesser-known name or aspect of Agni, the Vedic god of fire in Hindu mythology.
  • B. Adara
    Adara is a small coastal village on Atauro Island in East Timor, known for its traditional fishing community and nearby coral reefs popular with divers and snorkelers.
  • C. Zeleia
    Zeleia was an ancient city in the region of Mysia in northwestern Asia Minor, known from classical Greek and Roman historical and geographical sources.
  • D. Sylvana
    Sylvana is a feminine given name, often considered a variant of Silvana, typically associated with meanings related to forests or woodland.
  • E. Alithea
    Alithea is a virtuous and intelligent gentlewoman in William Wycherley’s Restoration comedy "The Country Wife," whose moral integrity contrasts with the play’s surrounding hypocrisy and sexual intrigue.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8eb84c48190b4f3bede254afde2 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4977cab4481909c6b94ca07cd5e4a completed April 19, 2026, 8:51 a.m.
NEDg Description generation batch_69e49d37989881909c7e75ddfff06726 completed April 19, 2026, 9:15 a.m.
NED2 Entity disambiguation (via description) batch_69e49f41a1f8819087cc15527dc7ff63 completed April 19, 2026, 9:24 a.m.
Created at: April 8, 2026, 9:30 p.m.