Triple

T24510902
Position Surface form Disambiguated ID Type / Status
Subject Theo Alice Ruggles Kitson E606213 entity
Predicate notableWork P4 FINISHED
Object The Hiker
The Hiker is a widely reproduced early 20th-century American war memorial statue by sculptor Theo Alice Ruggles Kitson, depicting a Spanish–American War soldier in the field.
E1638122 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: The Hiker | Statement: [Theo Alice Ruggles Kitson, notableWork, The Hiker]
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: The Hiker
Triple: [Theo Alice Ruggles Kitson, notableWork, The Hiker]
Generated description
The Hiker is a widely reproduced early 20th-century American war memorial statue by sculptor Theo Alice Ruggles Kitson, depicting a Spanish–American War soldier in the field.

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_69e2c4c725148190a4e41577c5cb409c completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a84bb4348190927f6dc8820321b0 completed April 30, 2026, 12:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee8f9da881908d1756de8761fb2e completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0fef20efe08190bb4cb412e2473ae5 completed May 22, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff097dd8881908bb83d84a6581ef7 completed May 22, 2026, 5:58 a.m.
Created at: April 18, 2026, 2:24 a.m.