Triple

T36355192
Position Surface form Disambiguated ID Type / Status
Subject Dadan E895322 entity
Predicate hasLanguage P15 FINISHED
Object Dadanitic language
The Dadanitic language is an ancient North Arabian script and dialect used in inscriptions from the oasis of Dadan (modern al-ʿUla) in northwestern Arabia during the first millennium BCE.
E2180133 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: Dadanitic language | Statement: [Dadan, hasLanguage, Dadanitic language]
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: Dadanitic language
Triple: [Dadan, hasLanguage, Dadanitic language]
Generated description
The Dadanitic language is an ancient North Arabian script and dialect used in inscriptions from the oasis of Dadan (modern al-ʿUla) in northwestern Arabia during the first millennium BCE.

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_69f76e5044248190b390d8887dc03254 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bac48dac8190b905b0dd3c739063 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a32c17148190a5b1e2dc959a304d completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a5b63d1881908583df97864d064b completed June 22, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_6a39a6dfc1c881909a4985813be8fcdd completed June 22, 2026, 9:19 p.m.
Created at: May 3, 2026, 4:09 p.m.