Triple

T4176793
Position Surface form Disambiguated ID Type / Status
Subject Skaro E86495 entity
Predicate hasContinent P233 FINISHED
Object Halldon
Halldon is a fictional continent on the planet Skaro in the Doctor Who universe, known as part of the Daleks’ homeworld geography.
 E418769 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: Halldon | Statement: [Skaro, hasContinent, Halldon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Halldon
Context triple: [Skaro, hasContinent, Halldon]
  • A. Lundenwic
    Lundenwic was the early medieval trading settlement and urban center of the Middle Saxons that preceded the later walled city of London.
  • B. Lealholm
    Lealholm is a small rural village in North Yorkshire, England, known for its picturesque setting in the Esk Valley within the North York Moors National Park.
  • C. Redenhall
    Redenhall is a small rural village and civil parish in the English county of Suffolk, known for its historic church and traditional countryside setting.
  • D. Hofuf
    Hofuf is a major oasis city in Saudi Arabia’s Al-Ahsa region, known for its extensive date palm groves, historic markets, and traditional architecture.
  • E. Eythorne
    Eythorne is a small village in Kent, England, known for its rural character and location near the port town of Dover.
  • 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: Halldon
Triple: [Skaro, hasContinent, Halldon]
Generated description
Halldon is a fictional continent on the planet Skaro in the Doctor Who universe, known as part of the Daleks’ homeworld geography.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Halldon
Target entity description: Halldon is a fictional continent on the planet Skaro in the Doctor Who universe, known as part of the Daleks’ homeworld geography.
  • A. Lundenwic
    Lundenwic was the early medieval trading settlement and urban center of the Middle Saxons that preceded the later walled city of London.
  • B. Lealholm
    Lealholm is a small rural village in North Yorkshire, England, known for its picturesque setting in the Esk Valley within the North York Moors National Park.
  • C. Redenhall
    Redenhall is a small rural village and civil parish in the English county of Suffolk, known for its historic church and traditional countryside setting.
  • D. Hofuf
    Hofuf is a major oasis city in Saudi Arabia’s Al-Ahsa region, known for its extensive date palm groves, historic markets, and traditional architecture.
  • E. Eythorne
    Eythorne is a small village in Kent, England, known for its rural character and location near the port town of Dover.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02eaa0d08190a3b805c64ef76a0c completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f564c9c8190bfc321c8ec2dac14 completed March 14, 2026, 3:31 p.m.
NEDg Description generation batch_69b58330b1d48190a3af96d3c0e7aa1b completed March 14, 2026, 3:48 p.m.
NED2 Entity disambiguation (via description) batch_69b583ba1fd8819092b7fe73a17dc406 completed March 14, 2026, 3:50 p.m.
Created at: March 9, 2026, 3:45 p.m.