Triple

T3407261
Position Surface form Disambiguated ID Type / Status
Subject Nabopolassar E71803 entity
Predicate predecessor P97 FINISHED
Object Kandalanu
Kandalanu was a late 7th-century BC king of Babylon, likely installed as a vassal ruler under the Assyrian Empire before the rise of Nabopolassar and the Neo-Babylonian dynasty.
 E355268 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: Kandalanu | Statement: [Nabopolassar, predecessor, Kandalanu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kandalanu
Context triple: [Nabopolassar, predecessor, Kandalanu]
  • A. Kandan
    Kandan is a locality within Beijing’s Fengtai District, known primarily as a residential and urban neighborhood area.
  • B. Kankia
    Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
  • C. Kandas
    Kandas is an Oceanic language of the Meso-Melanesian subgroup spoken in parts of Papua New Guinea.
  • D. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • E. Kanatal
    Kanatal is a serene hill station in Uttarakhand, India, known for its tranquil Himalayan views, apple orchards, and outdoor adventure activities.
  • 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: Kandalanu
Triple: [Nabopolassar, predecessor, Kandalanu]
Generated description
Kandalanu was a late 7th-century BC king of Babylon, likely installed as a vassal ruler under the Assyrian Empire before the rise of Nabopolassar and the Neo-Babylonian dynasty.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kandalanu
Target entity description: Kandalanu was a late 7th-century BC king of Babylon, likely installed as a vassal ruler under the Assyrian Empire before the rise of Nabopolassar and the Neo-Babylonian dynasty.
  • A. Kandan
    Kandan is a locality within Beijing’s Fengtai District, known primarily as a residential and urban neighborhood area.
  • B. Kankia
    Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
  • C. Kandas
    Kandas is an Oceanic language of the Meso-Melanesian subgroup spoken in parts of Papua New Guinea.
  • D. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • E. Kanatal
    Kanatal is a serene hill station in Uttarakhand, India, known for its tranquil Himalayan views, apple orchards, and outdoor adventure activities.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb8ede9c48190b13b0f5e7474e7fa completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdaf06c8190a8102a4e3c728066 completed March 12, 2026, 11:27 p.m.
NEDg Description generation batch_69b34e486c3c81908e73c5b75baf119c completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b34fc420b08190baee678721b1b32c completed March 12, 2026, 11:44 p.m.
Created at: March 8, 2026, 3:15 p.m.