Triple

T35966216
Position Surface form Disambiguated ID Type / Status
Subject Jaguar Mark X E1040149 entity
Predicate predecessor P97 FINISHED
Object Jaguar Mark IX
The Jaguar Mark IX is a late-1950s British luxury saloon car known for its stately styling, improved performance, and status as one of Jaguar’s classic flagship models of the era.
E2174605 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: Jaguar Mark IX | Statement: [Jaguar Mark X, predecessor, Jaguar Mark IX]
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: Jaguar Mark IX
Triple: [Jaguar Mark X, predecessor, Jaguar Mark IX]
Generated description
The Jaguar Mark IX is a late-1950s British luxury saloon car known for its stately styling, improved performance, and status as one of Jaguar’s classic flagship models of the era.

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_69f76e26b21081909fd9ffb3aff6c77a completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7abfcdb1c8190b4fabf807e31a1dc completed May 3, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d1c3efc819087824ebabf0c7ad2 completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a3950fd921c8190b5916677a78390b6 completed June 22, 2026, 3:13 p.m.
NED2 Entity disambiguation (via description) batch_6a39515cda948190a7b87dfe8fbfb48d completed June 22, 2026, 3:14 p.m.
Created at: May 3, 2026, 4:07 p.m.