Triple

T31579462
Position Surface form Disambiguated ID Type / Status
Subject Turkmen gul patterns E805782 entity
Predicate usedIn P98 FINISHED
Object Turkmen carpets
Turkmen carpets are traditional handwoven rugs from Turkmenistan and surrounding regions, renowned for their rich red tones, geometric motifs, and deep cultural and tribal significance.
E1979324 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: Turkmen carpets | Statement: [Turkmen gul patterns, usedIn, Turkmen carpets]
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: Turkmen carpets
Triple: [Turkmen gul patterns, usedIn, Turkmen carpets]
Generated description
Turkmen carpets are traditional handwoven rugs from Turkmenistan and surrounding regions, renowned for their rich red tones, geometric motifs, and deep cultural and tribal significance.

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_69f348d3a86c8190a3e5e539a4dd125f completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a8068ca0819098f9f0195b0eb125 completed May 3, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e6581ae8c81908eaccd89aae048d9 completed June 14, 2026, 8:25 a.m.
NEDg Description generation batch_6a2e66c0462881909c4d15469d7191e7 completed June 14, 2026, 8:30 a.m.
NED2 Entity disambiguation (via description) batch_6a2e67b73b308190826f4229c0eaa495 completed June 14, 2026, 8:35 a.m.
Created at: April 30, 2026, 10:22 p.m.