Triple

T24547172
Position Surface form Disambiguated ID Type / Status
Subject HR 4763 E607257 entity
Predicate alsoKnownAs P39 FINISHED
Object Gacrux
Gacrux is a bright red giant star that marks the top of the Southern Cross constellation and is one of the most prominent stars in the southern sky.
E148567 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: Gacrux | Statement: [HR 4763, alsoKnownAs, Gacrux]
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: Gacrux
Triple: [HR 4763, alsoKnownAs, Gacrux]
Generated description
Gacrux is a bright red giant star that marks the top of the Southern Cross constellation and is one of the most prominent stars in the southern sky.

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_69e2c4c9bf94819082d05da6f5c29907 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8caba8c819082c3bf33b6ff9cd0 completed April 30, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11ae85fac08190927f996ba9abdaae completed May 23, 2026, 1:41 p.m.
NEDg Description generation batch_6a11af4e7c608190a71debb7fc9c4b83 completed May 23, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a11b071a8c48190a3b486d471e3e1a1 completed May 23, 2026, 1:49 p.m.
Created at: April 18, 2026, 2:27 a.m.