Triple

T1836622
Position Surface form Disambiguated ID Type / Status
Subject Zazaki E41080 entity
Predicate hasScriptHistory P33959 FINISHED
Object Arabic script (historically) LITERAL 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: Arabic script (historically) | Statement: [Zazaki, hasScriptHistory, Arabic script (historically)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasScriptHistory
Context triple: [Zazaki, hasScriptHistory, Arabic script (historically)]
  • A. hasHistoricalRoute
    Indicates that an entity possesses or is associated with a route that has historical significance or origin.
  • B. hasWritingHistory
    Indicates that an entity has a recorded history or log of its writing-related actions, changes, or authored content over time.
  • C. hasPolicyHistory
    Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
  • D. hasHistoricalProcess
    Indicates that an entity is associated with, or characterized by, a historical process or sequence of events that unfolded over time.
  • E. hasProceduralHistory
    Indicates that an entity is associated with a record or sequence of procedural events, actions, or steps that have occurred over time.
  • F. None of above. chosen

Provenance (4 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb32d35508190bf1c487dffbecaf0 completed March 7, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69abafd88ebc81908208394746351fe6 completed March 7, 2026, 4:55 a.m.
PDg Predicate description generation batch_69abb32a8d548190a231c7c2ce276a5e completed March 7, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:33 p.m.