Triple

T26372830
Position Surface form Disambiguated ID Type / Status
Subject Edward Pakenham, 2nd Baron Longford E660816 entity
Predicate sibling P363 FINISHED
Object Elizabeth Pakenham
Elizabeth Pakenham was an Anglo-Irish noblewoman and member of the prominent Pakenham family associated with the Longford peerage.
E1736819 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: Elizabeth Pakenham | Statement: [Edward Pakenham, 2nd Baron Longford, sibling, Elizabeth Pakenham]
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: Elizabeth Pakenham
Triple: [Edward Pakenham, 2nd Baron Longford, sibling, Elizabeth Pakenham]
Generated description
Elizabeth Pakenham was an Anglo-Irish noblewoman and member of the prominent Pakenham family associated with the Longford peerage.

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_69ee812a698881908d6a58265995fa39 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f610310d7c8190a14a7f7aa377846a completed May 2, 2026, 2:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe5134a08190a7cd4780dfd1bb3c completed May 23, 2026, 7:21 p.m.
NEDg Description generation batch_6a11ff162d588190a1f98429d7fe5154 completed May 23, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a11ff99fdbc81909fd5646fb32987a2 completed May 23, 2026, 7:27 p.m.
Created at: April 26, 2026, 10:59 p.m.