Triple

T7680451
Position Surface form Disambiguated ID Type / Status
Subject The Emerald City of Oz E173977 entity
Predicate featuresSpecies P7733 FINISHED
Object Nomes
Nomes are a subterranean, gnome-like race of magical beings in L. Frank Baum’s Oz universe, typically depicted as miners and antagonists who covet precious metals and jewels.
 E680912 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: Nomes | Statement: [The Emerald City of Oz, featuresSpecies, Nomes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nomes
Context triple: [The Emerald City of Oz, featuresSpecies, Nomes]
  • A. Namnetes
    The Namnetes were an ancient Celtic tribe of western Gaul, associated with the region around modern Nantes in present-day France.
  • B. Nom
    Nom is a domain name marketplace and service platform operating under the brand Nom.com.
  • C. Nome
    Nome is a remote coastal city in western Alaska known historically for its gold rush heritage and as a key transportation and supply hub on the Bering Sea.
  • D. Nume
    Nume is an Oceanic language spoken on the island of Gaua in northern Vanuatu.
  • E. The Names
    The Names is a 1982 novel by Don DeLillo that blends political intrigue, linguistic obsession, and expatriate life in Greece and the Middle East into a meditative exploration of language, violence, and meaning.
  • 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: Nomes
Triple: [The Emerald City of Oz, featuresSpecies, Nomes]
Generated description
Nomes are a subterranean, gnome-like race of magical beings in L. Frank Baum’s Oz universe, typically depicted as miners and antagonists who covet precious metals and jewels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nomes
Target entity description: Nomes are a subterranean, gnome-like race of magical beings in L. Frank Baum’s Oz universe, typically depicted as miners and antagonists who covet precious metals and jewels.
  • A. Namnetes
    The Namnetes were an ancient Celtic tribe of western Gaul, associated with the region around modern Nantes in present-day France.
  • B. Nom
    Nom is a domain name marketplace and service platform operating under the brand Nom.com.
  • C. Nome
    Nome is a remote coastal city in western Alaska known historically for its gold rush heritage and as a key transportation and supply hub on the Bering Sea.
  • D. Nume
    Nume is an Oceanic language spoken on the island of Gaua in northern Vanuatu.
  • E. The Names
    The Names is a 1982 novel by Don DeLillo that blends political intrigue, linguistic obsession, and expatriate life in Greece and the Middle East into a meditative exploration of language, violence, and meaning.
  • 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_69c6995840408190a19de6c51090f46f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701ffc1fc8190bc9c2b1f3bb37f0d completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a24de3a48190a92009b6092b09d0 completed March 29, 2026, 3:53 a.m.
NEDg Description generation batch_69c8a30d3fac8190bec7e2748bc8f17e completed March 29, 2026, 3:57 a.m.
NED2 Entity disambiguation (via description) batch_69c8a3d2e660819099f90a9e43310381 completed March 29, 2026, 4 a.m.
Created at: March 27, 2026, 4:01 p.m.