Triple

T7326734
Position Surface form Disambiguated ID Type / Status
Subject Essex County Fire and Rescue Service E168894 entity
Predicate headquartersLocation P62 FINISHED
Object Rivenhall
Rivenhall is a village in Essex, England, notable for hosting the headquarters of the Essex County Fire and Rescue Service.
E656623 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: Rivenhall | Statement: [Essex County Fire and Rescue Service, headquartersLocation, Rivenhall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rivenhall
Context triple: [Essex County Fire and Rescue Service, headquartersLocation, Rivenhall]
  • A. Glaramara
    Glaramara is a prominent fell in England’s Lake District, known for its rugged ridges and extensive views over Borrowdale.
  • B. Ragnok
    Ragnok is a goblin associated with Gringotts Wizarding Bank in the Harry Potter universe, often depicted as a senior or influential figure among the goblins.
  • C. Lasham
    Lasham is a small rural village in Hampshire, England, best known for its large gliding airfield and aviation activities.
  • D. Eythorne
    Eythorne is a small village in Kent, England, known for its rural character and location near the port town of Dover.
  • E. Mythenquai
    Mythenquai is a popular lakeside recreational area in Zurich known for its swimming facilities, green spaces, and scenic views along Lake Zurich.
  • 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: Rivenhall
Triple: [Essex County Fire and Rescue Service, headquartersLocation, Rivenhall]
Generated description
Rivenhall is a village in Essex, England, notable for hosting the headquarters of the Essex County Fire and Rescue Service.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rivenhall
Target entity description: Rivenhall is a village in Essex, England, notable for hosting the headquarters of the Essex County Fire and Rescue Service.
  • A. Glaramara
    Glaramara is a prominent fell in England’s Lake District, known for its rugged ridges and extensive views over Borrowdale.
  • B. Ragnok
    Ragnok is a goblin associated with Gringotts Wizarding Bank in the Harry Potter universe, often depicted as a senior or influential figure among the goblins.
  • C. Lasham
    Lasham is a small rural village in Hampshire, England, best known for its large gliding airfield and aviation activities.
  • D. Eythorne
    Eythorne is a small village in Kent, England, known for its rural character and location near the port town of Dover.
  • E. Mythenquai
    Mythenquai is a popular lakeside recreational area in Zurich known for its swimming facilities, green spaces, and scenic views along Lake Zurich.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0a755e88190a50126e2d1d6d4cb completed March 27, 2026, 9:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ef0e3e7481908e6cedbd3f0077ca completed March 28, 2026, 3:09 p.m.
NEDg Description generation batch_69c7efa4f5148190842f30988cbea94c completed March 28, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69c7f0092bac819080ded1863f99290a completed March 28, 2026, 3:13 p.m.
Created at: March 27, 2026, 3:03 p.m.