Triple

T3777410
Position Surface form Disambiguated ID Type / Status
Subject Z 5600 E83340 entity
Predicate builder P3143 FINISHED
Object ANF
ANF is a French rolling stock manufacturer known for producing various types of railway vehicles and equipment.
 E387389 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: ANF | Statement: [Z 5600, builder, ANF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANF
Context triple: [Z 5600, builder, ANF]
  • A. ANP
    ANP is the national police force of Afghanistan responsible for law enforcement, public order, and internal security across the country.
  • B. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • C. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • D. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • E. ANA
    ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • 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: ANF
Triple: [Z 5600, builder, ANF]
Generated description
ANF is a French rolling stock manufacturer known for producing various types of railway vehicles and equipment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANF
Target entity description: ANF is a French rolling stock manufacturer known for producing various types of railway vehicles and equipment.
  • A. ANP
    ANP is the national police force of Afghanistan responsible for law enforcement, public order, and internal security across the country.
  • B. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • C. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • D. ANA
    ANA is the ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • E. ANA
    ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5d3dbc8190b6ab118a56acd5a3 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e534a02c8190b8dd76ed965f393f completed March 14, 2026, 4:33 a.m.
NEDg Description generation batch_69b4e6b1cefc8190971e9441dc145e19 completed March 14, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69b4ea8b9d2c819088db1fdf9dc90c0c completed March 14, 2026, 4:56 a.m.
Created at: March 8, 2026, 3:36 p.m.