Triple

T11729397
Position Surface form Disambiguated ID Type / Status
Subject Anniston Army Depot E278859 entity
Predicate hasAbbreviation P43 FINISHED
Object ANAD
ANAD is a major U.S. Army facility in Anniston, Alabama, known for maintenance, repair, and storage of military vehicles, weapons, and munitions.
 E942091 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: ANAD | Statement: [Anniston Army Depot, hasAbbreviation, ANAD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ANAD
Context triple: [Anniston Army Depot, hasAbbreviation, ANAD]
  • A. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • 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 Portuguese company responsible for managing and operating the main airports in Portugal.
  • 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 a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • 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: ANAD
Triple: [Anniston Army Depot, hasAbbreviation, ANAD]
Generated description
ANAD is a major U.S. Army facility in Anniston, Alabama, known for maintenance, repair, and storage of military vehicles, weapons, and munitions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ANAD
Target entity description: ANAD is a major U.S. Army facility in Anniston, Alabama, known for maintenance, repair, and storage of military vehicles, weapons, and munitions.
  • A. ANA
    ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
  • 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 ICAO airline designator for All Nippon Airways, Japan’s largest airline and a major global carrier.
  • D. ANA
    ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
  • E. ANA
    ANA is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4d80ef881908cab956787ab07fd completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef83f98fc481908015df3c4e5d7ed3 completed April 27, 2026, 3:42 p.m.
NEDg Description generation batch_69ef9b68309081909f3f614efeeb2ab1 completed April 27, 2026, 5:22 p.m.
NED2 Entity disambiguation (via description) batch_69efd6aba82c81909ff22e6b26db3cfe completed April 27, 2026, 9:35 p.m.
Created at: April 8, 2026, 9:41 p.m.