Triple

T34437518
Position Surface form Disambiguated ID Type / Status
Subject Lewt McCanles E884002 entity
Predicate settingOfActivity P1957 FINISHED
Object Texas ranch
The Texas ranch is a sprawling, rugged cattle property that serves as the primary backdrop for Lewt McCanles’s frontier life and conflicts.
E2097406 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: Texas ranch | Statement: [Lewt McCanles, settingOfActivity, Texas ranch]
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: Texas ranch
Triple: [Lewt McCanles, settingOfActivity, Texas ranch]
Generated description
The Texas ranch is a sprawling, rugged cattle property that serves as the primary backdrop for Lewt McCanles’s frontier life and conflicts.

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_69f349c548d88190978e2a82502c03d0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71912238c8190a15b0de2139fa2bf completed May 3, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3718362d2c8190a4c4ad11a0df0cdb completed June 20, 2026, 10:46 p.m.
NEDg Description generation batch_6a371915ed9481908ec07df96defbd04 completed June 20, 2026, 10:49 p.m.
NED2 Entity disambiguation (via description) batch_6a371997701081908d9fe75e9692f47e completed June 20, 2026, 10:52 p.m.
Created at: May 1, 2026, 2 a.m.