Triple

T23768425
Position Surface form Disambiguated ID Type / Status
Subject Szekszárd E587450 entity
Predicate hasCoatOfArms P1663 FINISHED
Object Coat of arms of Szekszárd
The Coat of arms of Szekszárd is the official heraldic emblem representing the Hungarian city of Szekszárd, reflecting its historical and cultural identity.
E1602280 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: Coat of arms of Szekszárd | Statement: [Szekszárd, hasCoatOfArms, Coat of arms of Szekszárd]
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: Coat of arms of Szekszárd
Triple: [Szekszárd, hasCoatOfArms, Coat of arms of Szekszárd]
Generated description
The Coat of arms of Szekszárd is the official heraldic emblem representing the Hungarian city of Szekszárd, reflecting its historical and cultural identity.

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_69e2490b8ac48190a6b35f1d5500486b completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1c4638b248190b512841493778483 completed April 29, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53e03d54819083a3ae28425e2e36 completed May 21, 2026, 6:50 p.m.
NEDg Description generation batch_6a0f58a53a2c8190b21b388d82aee594 completed May 21, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_6a0f5a1bfb008190b49890182d0b59de completed May 21, 2026, 7:16 p.m.
Created at: April 17, 2026, 7:15 p.m.