Triple

T10244413
Position Surface form Disambiguated ID Type / Status
Subject Halle Bailey E240175 entity
Predicate givenName P17 FINISHED
Object Halle
Halle is a feminine given name used in various cultures, notably borne by American actress and singer Halle Bailey.
 E853558 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: Halle | Statement: [Halle Bailey, givenName, Halle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Halle
Context triple: [Halle Bailey, givenName, Halle]
  • A. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • B. Halle
    Halle is a historic city in the Belgian province of Flemish Brabant, known for its medieval architecture and the Basilica of Saint Martin, a notable pilgrimage site.
  • C. Halle (Saale)
    Halle (Saale) is a major city in the German state of Saxony-Anhalt, known as an important economic, cultural, and educational center, including being home to the Martin Luther University of Halle-Wittenberg.
  • D. Blentheim
    Blentheim is a location in New Zealand that serves as one of the seats of the High Court of New Zealand.
  • E. Hallen
    Hallen is a small village in South Gloucestershire, England, situated near Bristol and known for its rural character and proximity to major transport routes.
  • 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: Halle
Triple: [Halle Bailey, givenName, Halle]
Generated description
Halle is a feminine given name used in various cultures, notably borne by American actress and singer Halle Bailey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Halle
Target entity description: Halle is a feminine given name used in various cultures, notably borne by American actress and singer Halle Bailey.
  • A. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • B. Halle
    Halle is a historic city in the Belgian province of Flemish Brabant, known for its medieval architecture and the Basilica of Saint Martin, a notable pilgrimage site.
  • C. Halle (Saale)
    Halle (Saale) is a major city in the German state of Saxony-Anhalt, known as an important economic, cultural, and educational center, including being home to the Martin Luther University of Halle-Wittenberg.
  • D. Blentheim
    Blentheim is a location in New Zealand that serves as one of the seats of the High Court of New Zealand.
  • E. Hallen
    Hallen is a small village in South Gloucestershire, England, situated near Bristol and known for its rural character and proximity to major transport routes.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d22a76188190a73df23bfb08eb3d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7936ce4819087f07df2c7a76282 completed April 9, 2026, 12:49 a.m.
NEDg Description generation batch_69d6fa2f7a848190a9de5de4d0f3f110 completed April 9, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69d6fcbab3ec8190ade1c0223c22ad58 completed April 9, 2026, 1:11 a.m.
Created at: April 6, 2026, 11:26 a.m.