Triple

T23048176
Position Surface form Disambiguated ID Type / Status
Subject Battle of Pákozd E573935 entity
Predicate commander P1061 FINISHED
Object János Móga
János Móga was a Hungarian general who played a key leadership role in the early stages of the Hungarian Revolution of 1848.
E1704992 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: János Móga | Statement: [Battle of Pákozd, commander, János Móga]
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: János Móga
Triple: [Battle of Pákozd, commander, János Móga]
Generated description
János Móga was a Hungarian general who played a key leadership role in the early stages of the Hungarian Revolution of 1848.

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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1867a206c81909ff923cbf56f7787 completed April 29, 2026, 4:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1107344f7c8190bb8d4b75d68cb669 completed May 23, 2026, 1:47 a.m.
NEDg Description generation batch_6a110a2092e08190a0449f88ae116299 completed May 23, 2026, 2 a.m.
NED2 Entity disambiguation (via description) batch_6a110b07ed44819083f71d43b4811cfe completed May 23, 2026, 2:03 a.m.
Created at: April 17, 2026, 3:54 p.m.