Triple

T31812768

Position	Surface form	Disambiguated ID	Type / Status
Subject	Hamburger Derby	`E812050`	entity
Predicate	derbyBetween	`P68699`	FINISHED
Object	Hamburger SV and FC St. Pauli Hamburger SV and FC St. Pauli are the two rival football clubs from Hamburg whose intense local clashes form one of Germany’s most famous city derbies.	`E1999693`	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: Hamburger SV and FC St. Pauli | Statement: [Hamburger Derby, derbyBetween, Hamburger SV and FC St. Pauli]

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: Hamburger SV and FC St. Pauli
Triple: [Hamburger Derby, derbyBetween, Hamburger SV and FC St. Pauli]

Generated description

Hamburger SV and FC St. Pauli are the two rival football clubs from Hamburg whose intense local clashes form one of Germany’s most famous city derbies.

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_69f348e846c081908eb468a0665afd55`	completed	April 30, 2026, 12:19 p.m.
NER	Named-entity recognition	`batch_69f6acf98f108190840c5ec4f6031e40`	completed	May 3, 2026, 2:03 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2f46b1602c8190a7cd3a59c380e59c`	completed	June 15, 2026, 12:26 a.m.
NEDg	Description generation	`batch_6a2f4aa3d64481908a3252f02d4c752a`	completed	June 15, 2026, 12:43 a.m.
NED2	Entity disambiguation (via description)	`batch_6a2f4aff2aa48190984dcbf5f3bffd86`	completed	June 15, 2026, 12:44 a.m.

Created at: April 30, 2026, 11:44 p.m.