Triple

T24106296
Position Surface form Disambiguated ID Type / Status
Subject Baron Chelmsford E597235 entity
Predicate hasHolder P1911 FINISHED
Object Ernest Thesiger, 4th Baron Chelmsford
Ernest Thesiger, 4th Baron Chelmsford, was a British peer who held the hereditary title in the Chelmsford barony.
E1631168 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: Ernest Thesiger, 4th Baron Chelmsford | Statement: [Baron Chelmsford, hasHolder, Ernest Thesiger, 4th Baron Chelmsford]
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: Ernest Thesiger, 4th Baron Chelmsford
Triple: [Baron Chelmsford, hasHolder, Ernest Thesiger, 4th Baron Chelmsford]
Generated description
Ernest Thesiger, 4th Baron Chelmsford, was a British peer who held the hereditary title in the Chelmsford barony.

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_69e288c60f9c8190af948d7354aedbeb completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1de170ee88190a6d57482651f7da9 completed April 29, 2026, 10:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd6397660819080ef6b55625576a5 completed May 22, 2026, 4:06 a.m.
NEDg Description generation batch_6a0fd7f84a908190a128494e4b442ada completed May 22, 2026, 4:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd8d0f6848190a77aff96b4fbcc3d completed May 22, 2026, 4:17 a.m.
Created at: April 17, 2026, 11:01 p.m.