Triple

T17989428
Position Surface form Disambiguated ID Type / Status
Subject Burrum Heads E430327 entity
Predicate nearbyTown P3883 FINISHED
Object Howard
Howard is a small rural town in Queensland, Australia, known for its historic buildings and quiet, community-focused lifestyle.
E429431 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: Howard | Statement: [Burrum Heads, nearbyTown, Howard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard
Context triple: [Burrum Heads, nearbyTown, Howard]
  • A. Howard
    Howard is the given name of the influential American film director, producer, and screenwriter Howard Hawks.
  • B. Howard
    Howard is a common English surname shared by numerous notable figures across entertainment, politics, and other fields.
  • C. Howard
    Howard is a young boy who serves as a minor but symbolically important character in the play "Inherit the Wind," representing the town’s impressionable youth amid the evolution-versus-creationism trial.
  • D. Howard
    Howard is one of Sethe’s sons in Toni Morrison’s novel "Beloved," a child whose life is shaped by the trauma and legacy of slavery.
  • E. Howard
    Howard is a character in Kenneth Lonergan's play "The Waverly Gallery," serving as a key figure in the story's exploration of family, memory, and aging.
  • 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: Howard
Triple: [Burrum Heads, nearbyTown, Howard]
Generated description
Howard is a small rural town in Queensland, Australia, known for its historic buildings and quiet, community-focused lifestyle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Howard
Target entity description: Howard is a small rural town in Queensland, Australia, known for its historic buildings and quiet, community-focused lifestyle.
  • A. Howard chosen
    Howard is a small rural town in Queensland, Australia, known historically for coal mining and situated within the Fraser Coast Region.
  • B. Howard
    Howard is a former U.S. Air Force base area near Panama City, Panama, now redeveloped as a mixed-use community and business hub.
  • C. Howard
    Howard is a young boy who serves as a minor but symbolically important character in the play "Inherit the Wind," representing the town’s impressionable youth amid the evolution-versus-creationism trial.
  • D. Howard
    Howard is a character in Kenneth Lonergan's play "The Waverly Gallery," serving as a key figure in the story's exploration of family, memory, and aging.
  • E. Howard
    Howard is the protagonist of the horror novel "The Keep," around whom the story’s supernatural and psychological events revolve.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b29e47a88190be58b79c73d3e652 completed April 19, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0337acabd481909deced9a61d84ed3 completed May 12, 2026, 2:22 p.m.
NEDg Description generation batch_6a0338cd02808190b650f59fc16bab0d completed May 12, 2026, 2:27 p.m.
NED2 Entity disambiguation (via description) batch_6a033cb498248190a3805cd356832cd0 completed May 12, 2026, 2:44 p.m.
Created at: April 10, 2026, 10:23 a.m.