Triple

T23587439

Position	Surface form	Disambiguated ID	Type / Status
Subject	Capture of Brielle	`E582384`	entity
Predicate	commanderOrLeader	`P1197`	FINISHED
Object	Lumey, Count of La Marck Lumey, Count of La Marck was a 16th-century Dutch nobleman and rebel leader of the Sea Beggars who played a key role in the early stages of the Dutch Revolt against Spanish rule.	`E1596736`	NE FINISHED

How this triple was built (3 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: Lumey, Count of La Marck | Statement: [Capture of Brielle, commanderOrLeader, Lumey, Count of La Marck]

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: Lumey, Count of La Marck
Triple: [Capture of Brielle, commanderOrLeader, Lumey, Count of La Marck]

Generated description

Lumey, Count of La Marck was a 16th-century Dutch nobleman and rebel leader of the Sea Beggars who played a key role in the early stages of the Dutch Revolt against Spanish rule.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: commanderOrLeader
Context triple: [Capture of Brielle, commanderOrLeader, Lumey, Count of La Marck]

A. commander
Indicates that one entity holds authoritative military or organizational control over another entity or group.
B. hasCommander chosen
Indicates that one entity serves as the commanding officer or leader of another entity.
C. hasCommanderRank
Indicates that an entity holds the military or organizational rank of commander within a specified hierarchy or context.
D. commanderAlsoServesAs
Indicates that the person who holds a commander role simultaneously fulfills one or more additional official roles or positions.
E. commanderOfVictoriousSide
Indicates that one entity served as the commanding leader of the side that achieved victory in a conflict or competition relative to another entity.
F. None of above.

Provenance (6 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_69e248f8d8248190acd5aee77f0d1709`	completed	April 17, 2026, 2:51 p.m.
NER	Named-entity recognition	`batch_69f1b0329f808190b158c9bf68d4fd35`	completed	April 29, 2026, 7:16 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0f4579661481909bdd0bb741218173`	completed	May 21, 2026, 5:48 p.m.
NEDg	Description generation	`batch_6a0f494fc8f08190a2846b4a9ab5d517`	completed	May 21, 2026, 6:05 p.m.
NED2	Entity disambiguation (via description)	`batch_6a0f49f4141c8190a9ae06e9d4ce7722`	completed	May 21, 2026, 6:07 p.m.
PD	Predicate disambiguation	`batch_69f118c96a0081908a8ac98ef7e7e60c`	completed	April 28, 2026, 8:30 p.m.

Created at: April 17, 2026, 6:41 p.m.