Triple

T563855
Position Surface form Disambiguated ID Type / Status
Subject Central Tablelands E13510 entity
Predicate contains P35 FINISHED
Object Orange
Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
 E70926 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: Orange | Statement: [Central Tablelands, contains, Orange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orange
Context triple: [Central Tablelands, contains, Orange]
  • A. Orange
    Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
  • B. Blue
    Blue is a critically acclaimed 1971 folk album by Joni Mitchell, widely regarded as one of the greatest and most influential records in popular music history.
  • C. Blue
    Blue is the anthropomorphic blue horse who serves as the official mascot of the NFL’s Indianapolis Colts.
  • D. Red
    Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
  • E. Crimson
    Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
  • 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: Orange
Triple: [Central Tablelands, contains, Orange]
Generated description
Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orange
Target entity description: Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
  • A. Orange
    Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
  • B. Blue
    Blue is a critically acclaimed 1971 folk album by Joni Mitchell, widely regarded as one of the greatest and most influential records in popular music history.
  • C. Blue
    Blue is the anthropomorphic blue horse who serves as the official mascot of the NFL’s Indianapolis Colts.
  • D. Red
    Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
  • E. Crimson
    Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49a712bc48190ba298b3c76ab11cc completed March 1, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4efcf05b88190a0fc2f2e86834248 completed March 2, 2026, 2:02 a.m.
NEDg Description generation batch_69a4f07f6f2c819088513b9172618066 completed March 2, 2026, 2:05 a.m.
NED2 Entity disambiguation (via description) batch_69a4f10b8bd0819082768fbe8213111f completed March 2, 2026, 2:08 a.m.
Created at: March 1, 2026, 7:32 p.m.