Triple

T30713425
Position Surface form Disambiguated ID Type / Status
Subject Anne Lockhart E781955 entity
Predicate positionHeld P8 FINISHED
Object Countess of Aberdeen
The Countess of Aberdeen is a Scottish noble title in the Peerage of Scotland historically associated with the Gordon family and the Aberdeenshire estate of Haddo House.
E1959845 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: Countess of Aberdeen | Statement: [Anne Lockhart, positionHeld, Countess of Aberdeen]
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: Countess of Aberdeen
Triple: [Anne Lockhart, positionHeld, Countess of Aberdeen]
Generated description
The Countess of Aberdeen is a Scottish noble title in the Peerage of Scotland historically associated with the Gordon family and the Aberdeenshire estate of Haddo House.

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_69f224acd24481908ed5f96f0d69b5dd completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c20d09481908f566241722507d3 completed May 2, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2ad2122e94819082f1165d47ee653a completed June 11, 2026, 3:19 p.m.
NEDg Description generation batch_6a2ad6480dac8190a8b57287ec1faea2 completed June 11, 2026, 3:37 p.m.
NED2 Entity disambiguation (via description) batch_6a2adc7df34c819094e953fa8fbd34ab completed June 11, 2026, 4:04 p.m.
Created at: April 29, 2026, 8:35 p.m.