Triple

T7557966
Position Surface form Disambiguated ID Type / Status
Subject Actors' Equity Association E178719 entity
Predicate hasOffice P1268 FINISHED
Object Orlando
Orlando is a major city in central Florida known for its tourism industry, theme parks, and entertainment sector.
 E11265 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: Orlando | Statement: [Actors' Equity Association, hasOffice, Orlando]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orlando
Context triple: [Actors' Equity Association, hasOffice, Orlando]
  • A. Orlando
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a 1992 British period fantasy film, based on Virginia Woolf’s novel, in which Tilda Swinton plays an androgynous noble who lives for centuries while changing gender.
  • C. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • D. Orlando
    Orlando is the Italian literary counterpart of the medieval knight Roland, best known as the chivalric hero of epic poems such as "Orlando Furioso."
  • E. Orlando
    Orlando is a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • 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: Orlando
Triple: [Actors' Equity Association, hasOffice, Orlando]
Generated description
Orlando is a major city in central Florida known for its tourism industry, theme parks, and entertainment sector.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orlando
Target entity description: Orlando is a major city in central Florida known for its tourism industry, theme parks, and entertainment sector.
  • A. Orlando chosen
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • C. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • D. Orlando
    Orlando is the young, virtuous, and romantically idealistic hero of Shakespeare’s comedy "As You Like It," known for his love for Rosalind and his conflict with his elder brother.
  • E. Orlando
    Orlando is the Italian literary counterpart of the medieval knight Roland, best known as the chivalric hero of epic poems such as "Orlando Furioso."
  • F. None of above.

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_69c69f2da22c8190a50942ac20af70e8 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8db3d508190850ed41854d69838 completed March 27, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870780d24819095196cd3a22bec5a completed March 29, 2026, 12:21 a.m.
NEDg Description generation batch_69c8725e42a481909bf442987fca3a8c completed March 29, 2026, 12:29 a.m.
NED2 Entity disambiguation (via description) batch_69c872f89ff08190809d476ae6809488 completed March 29, 2026, 12:31 a.m.
Created at: March 27, 2026, 3:50 p.m.