Triple

T26774664
Position Surface form Disambiguated ID Type / Status
Subject Hovhannes Tumanyan E670084 entity
Predicate notableWork P4 FINISHED
Object The Dog and the Cat
"The Dog and the Cat" is a famous humorous fable in verse by Armenian writer Hovhannes Tumanyan that explores friendship, conflict, and reconciliation through the antics of its animal protagonists.
 E1741197 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: The Dog and the Cat | Statement: [Hovhannes Tumanyan, notableWork, The Dog and the Cat]
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: The Dog and the Cat
Triple: [Hovhannes Tumanyan, notableWork, The Dog and the Cat]
Generated description
"The Dog and the Cat" is a famous humorous fable in verse by Armenian writer Hovhannes Tumanyan that explores friendship, conflict, and reconciliation through the antics of its animal protagonists.

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_69eeb31c925881909b597f6e40056d28 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f6193170a88190adbbb22150475bb5 completed May 2, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1209581948819096c70dcfc1d51245 completed May 23, 2026, 8:08 p.m.
NEDg Description generation batch_6a120a567424819083cc2364aa6ec9da completed May 23, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_6a120b5561cc81909195b6d74ec74b50 completed May 23, 2026, 8:17 p.m.
Created at: April 27, 2026, 4:04 a.m.