Triple

T24461234
Position Surface form Disambiguated ID Type / Status
Subject Herneith E616831 entity
Predicate associatedWith P37 FINISHED
Object King Den
King Den was an early pharaoh of ancient Egypt’s First Dynasty, known for consolidating royal power and being among the first rulers depicted wearing the double crown of Upper and Lower Egypt.
E1634329 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: King Den | Statement: [Herneith, associatedWith, King Den]
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: King Den
Triple: [Herneith, associatedWith, King Den]
Generated description
King Den was an early pharaoh of ancient Egypt’s First Dynasty, known for consolidating royal power and being among the first rulers depicted wearing the double crown of Upper and Lower Egypt.

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_69e2d7ef9fe08190a0613908758b4e86 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f298ca59088190a657c863713a9eb0 completed April 29, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe38c54b081909f7b9c87dda15d59 completed May 22, 2026, 5:03 a.m.
NEDg Description generation batch_6a0fe53e515c8190906ddea7df4df7a8 completed May 22, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe5d61ffc819090ded9351ea9066d completed May 22, 2026, 5:12 a.m.
Created at: April 18, 2026, 2:19 a.m.