Triple

T32790703
Position Surface form Disambiguated ID Type / Status
Subject ruins of Nicaea E838617 entity
Predicate hasPart P35 FINISHED
Object ancient theatre of Nicaea
The ancient theatre of Nicaea is a Greco-Roman performance venue whose remains form part of the archaeological ruins of the historic city of Nicaea in modern-day Turkey.
E2024634 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: ancient theatre of Nicaea | Statement: [ruins of Nicaea, hasPart, ancient theatre of Nicaea]
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: ancient theatre of Nicaea
Triple: [ruins of Nicaea, hasPart, ancient theatre of Nicaea]
Generated description
The ancient theatre of Nicaea is a Greco-Roman performance venue whose remains form part of the archaeological ruins of the historic city of Nicaea in modern-day Turkey.

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_69f3493c7f6881908edf2aa13631d1e0 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cd76547881909e21647679f45e72 completed May 3, 2026, 4:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b16a42f8819086fd0b7a7991d768 completed June 19, 2026, 3:03 a.m.
NEDg Description generation batch_6a34b1d9088481908cd983c150f8215e completed June 19, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_6a34b24078088190b8e38b1d8302cef1 completed June 19, 2026, 3:06 a.m.
Created at: May 1, 2026, 1:14 a.m.