Triple

T25271696
Position Surface form Disambiguated ID Type / Status
Subject Simalia E633584 entity
Predicate hasMember P10 FINISHED
Object Boelen’s python
Boelen’s python is a large, nonvenomous python species from New Guinea, notable for its iridescent dark scales and popularity among reptile enthusiasts.
 E1686029 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: Boelen’s python | Statement: [Simalia, hasMember, Boelen’s python]
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: Boelen’s python
Triple: [Simalia, hasMember, Boelen’s python]
Generated description
Boelen’s python is a large, nonvenomous python species from New Guinea, notable for its iridescent dark scales and popularity among reptile enthusiasts.

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_69e75a92f48881909974ff9c11150a2e completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f48ba2bb608190bb26a5a496fff3b8 completed May 1, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c117961081908a667d2053857a3d completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c4eb37cc8190b7c3440b77e8336e completed May 22, 2026, 9:04 p.m.
NED2 Entity disambiguation (via description) batch_6a10c5487a008190aa865554f445ab5e completed May 22, 2026, 9:06 p.m.
Created at: April 21, 2026, 1:16 p.m.