Triple

T35065837
Position Surface form Disambiguated ID Type / Status
Subject Amanda Ripley E1011727 entity
Predicate appearsIn P795 FINISHED
Object Alien: Into Charybdis
Alien: Into Charybdis is a science fiction horror novel set in the Alien franchise universe, following a deadly xenomorph outbreak amid political tensions and corporate intrigue.
E2132205 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: Alien: Into Charybdis | Statement: [Amanda Ripley, appearsIn, Alien: Into Charybdis]
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: Alien: Into Charybdis
Triple: [Amanda Ripley, appearsIn, Alien: Into Charybdis]
Generated description
Alien: Into Charybdis is a science fiction horror novel set in the Alien franchise universe, following a deadly xenomorph outbreak amid political tensions and corporate intrigue.

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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78613f9dc8190b20a15c22090d27f completed May 3, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380f9114d48190a6b48e4e7bbc81be completed June 21, 2026, 4:21 p.m.
NEDg Description generation batch_6a3813552a208190b8e37c1f109aa589 completed June 21, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_6a3813f1f984819081860c509642ee1d completed June 21, 2026, 4:40 p.m.
Created at: May 3, 2026, 4:01 p.m.