Triple

T3446477
Position Surface form Disambiguated ID Type / Status
Subject Nabonidus E72689 entity
Predicate residence P75 FINISHED
Object Tayma E255451 NE FINISHED

How this triple was built (2 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: Tayma | Statement: [Nabonidus, residence, Tayma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tayma
Context triple: [Nabonidus, residence, Tayma]
  • A. Tayma chosen
    Tayma is an ancient oasis town in northwestern Saudi Arabia known for its significant archaeological remains and long history as a caravan and trade center.
  • B. Tamahaq
    Tamahaq is a Berber (Amazigh) language traditionally spoken by the Tuareg people of the central Sahara.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Tadlac
    Tadlac is a barangay in the municipality of Los Baños in Laguna province, Philippines, known for its proximity to Tadlac Lake (also called Alligator Lake).
  • E. Tribeni
    Tribeni is a town in West Bengal, India, historically known as a sacred confluence point of rivers and an important riverside settlement.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba6efb188190b989fa4d6f28e16b completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360e32ba08190bcd2f3cbe963c443 completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:16 p.m.