Triple

T27964359
Position Surface form Disambiguated ID Type / Status
Subject Liberty Cap E704674 entity
Predicate category P87 FINISHED
Object Travertine cone
A travertine cone is a steep, conical mound of calcium carbonate deposited by mineral-rich hot spring waters, often forming prominent geothermal features in areas like Yellowstone National Park.
E1796992 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: Travertine cone | Statement: [Liberty Cap, category, Travertine cone]
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: Travertine cone
Triple: [Liberty Cap, category, Travertine cone]
Generated description
A travertine cone is a steep, conical mound of calcium carbonate deposited by mineral-rich hot spring waters, often forming prominent geothermal features in areas like Yellowstone National Park.

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_69ef841061e48190b5570f9562f7434d completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63b058f6c8190af423aae815a0599 completed May 2, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a131171659881908fe7295d4a8e73e7 completed May 24, 2026, 2:55 p.m.
NEDg Description generation batch_6a13123ff90c8190990bfee6acf6bec0 completed May 24, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_6a1313b4fa4c81909b37b7a51f926f45 completed May 24, 2026, 3:05 p.m.
Created at: April 27, 2026, 7:34 p.m.