Triple

T8925566
Position Surface form Disambiguated ID Type / Status
Subject Lagash E212531 entity
Predicate majorDeity P7648 FINISHED
Object Nanshe
Nanshe is a Mesopotamian goddess associated primarily with social justice, divination, and the protection of the vulnerable.
 E770332 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: Nanshe | Statement: [Lagash, majorDeity, Nanshe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nanshe
Context triple: [Lagash, majorDeity, Nanshe]
  • A. Ur-Nanshe
    Ur-Nanshe was an early dynastic king of the Sumerian city-state of Lagash, known for temple construction and establishing Lagash as a significant regional power.
  • B. Enheduanna
    Enheduanna was an Akkadian high priestess and poet from the 23rd century BCE, widely regarded as the earliest known named author in world history.
  • C. Seshemetka
    Seshemetka was an early ancient Egyptian queen consort of the 1st Dynasty, known primarily as a wife of King Djer.
  • D. Tashmetu-sharrat
    Tashmetu-sharrat was a Neo-Assyrian queen and consort of King Sennacherib, known from royal inscriptions and administrative records of his reign.
  • E. Henutsen
    Henutsen was an ancient Egyptian queen of the 4th Dynasty, best known as one of Pharaoh Khufu’s consorts and likely the mother of several of his children.
  • 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: Nanshe
Triple: [Lagash, majorDeity, Nanshe]
Generated description
Nanshe is a Mesopotamian goddess associated primarily with social justice, divination, and the protection of the vulnerable.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nanshe
Target entity description: Nanshe is a Mesopotamian goddess associated primarily with social justice, divination, and the protection of the vulnerable.
  • A. Ur-Nanshe
    Ur-Nanshe was an early dynastic king of the Sumerian city-state of Lagash, known for temple construction and establishing Lagash as a significant regional power.
  • B. Enheduanna
    Enheduanna was an Akkadian high priestess and poet from the 23rd century BCE, widely regarded as the earliest known named author in world history.
  • C. Seshemetka
    Seshemetka was an early ancient Egyptian queen consort of the 1st Dynasty, known primarily as a wife of King Djer.
  • D. Tashmetu-sharrat
    Tashmetu-sharrat was a Neo-Assyrian queen and consort of King Sennacherib, known from royal inscriptions and administrative records of his reign.
  • E. Henutsen
    Henutsen was an ancient Egyptian queen of the 4th Dynasty, best known as one of Pharaoh Khufu’s consorts and likely the mother of several of his children.
  • 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_69ca839481d48190b42b037e0d0f636c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66700fb48190874563e535f20437 completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc932f9848190a2571cfc28353088 completed April 3, 2026, 2:05 p.m.
NEDg Description generation batch_69cfcd15fa94819081631852f3e46d86 completed April 3, 2026, 2:22 p.m.
NED2 Entity disambiguation (via description) batch_69cfcd90c21481908f59e3fc2924421d completed April 3, 2026, 2:24 p.m.
Created at: March 30, 2026, 6:57 p.m.