Triple

T7289343
Position Surface form Disambiguated ID Type / Status
Subject Positions E163951 entity
Predicate producer P490 FINISHED
Object Neshann
Neshann is a music producer known for creating and arranging tracks, often working behind the scenes to shape the sound and direction of recorded songs.
 E653102 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: Neshann | Statement: [Positions, producer, Neshann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neshann
Context triple: [Positions, producer, Neshann]
  • A. Natuashish
    Natuashish is a remote Innu community in northern Labrador, Canada, established as a replacement for the former settlement of Davis Inlet.
  • B. Nese
    Nese is an endangered Oceanic language spoken by a small community on the island of Malakula in Vanuatu.
  • C. Nowshak
    Nowshak is the highest mountain in Afghanistan and the second-highest peak in the Hindu Kush range.
  • D. Nisenan
    The Nisenan are an Indigenous people of Northern California, traditionally inhabiting the Sierra Nevada foothills and Sacramento Valley, with a distinct Maidu language and culture.
  • E. Verna
    Verna is a feminine given name that gained particular recognition through film editor Verna Fields, known for her work on movies like "Jaws."
  • 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: Neshann
Triple: [Positions, producer, Neshann]
Generated description
Neshann is a music producer known for creating and arranging tracks, often working behind the scenes to shape the sound and direction of recorded songs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neshann
Target entity description: Neshann is a music producer known for creating and arranging tracks, often working behind the scenes to shape the sound and direction of recorded songs.
  • A. Natuashish
    Natuashish is a remote Innu community in northern Labrador, Canada, established as a replacement for the former settlement of Davis Inlet.
  • B. Nese
    Nese is an endangered Oceanic language spoken by a small community on the island of Malakula in Vanuatu.
  • C. Nowshak
    Nowshak is the highest mountain in Afghanistan and the second-highest peak in the Hindu Kush range.
  • D. Nisenan
    The Nisenan are an Indigenous people of Northern California, traditionally inhabiting the Sierra Nevada foothills and Sacramento Valley, with a distinct Maidu language and culture.
  • E. Verna
    Verna is a feminine given name that gained particular recognition through film editor Verna Fields, known for her work on movies like "Jaws."
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb6bde448190b52852c916a8059d completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db4a31608190ba465e22e7a81782 completed March 28, 2026, 1:44 p.m.
NEDg Description generation batch_69c7dbf65fb08190ae8a9c4e57d42e97 completed March 28, 2026, 1:47 p.m.
NED2 Entity disambiguation (via description) batch_69c7dc6af4b08190be165856d216f2ae completed March 28, 2026, 1:49 p.m.
Created at: March 27, 2026, 3 p.m.