Triple

T29446773
Position Surface form Disambiguated ID Type / Status
Subject Tyrrellspass E746873 entity
Predicate hasHistoricalAssociation P2834 FINISHED
Object Tyrrell family
The Tyrrell family is an Anglo-Norman lineage historically prominent in Ireland and England, known for its medieval landholdings, military roles, and enduring local influence.
E1865963 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: Tyrrell family | Statement: [Tyrrellspass, hasHistoricalAssociation, Tyrrell family]
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: Tyrrell family
Triple: [Tyrrellspass, hasHistoricalAssociation, Tyrrell family]
Generated description
The Tyrrell family is an Anglo-Norman lineage historically prominent in Ireland and England, known for its medieval landholdings, military roles, and enduring local influence.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66b2124b08190a88f01f19caee6cf completed May 2, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d93b4e4081909115db1a67f5d155 completed June 7, 2026, 8:48 p.m.
NEDg Description generation batch_6a25ddc9250c81909699e77c8632f6a4 completed June 7, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a25de928df48190978f5b3b317a955d completed June 7, 2026, 9:11 p.m.
Created at: April 28, 2026, 3:28 p.m.