Triple

T4922130
Position Surface form Disambiguated ID Type / Status
Subject W4 star-forming region E110488 entity
Predicate catalogDesignation P974 FINISHED
Object W4
W4 is a prominent star-forming region in the Milky Way, notable for its large ionized gas bubble and active formation of massive young stars.
 E480049 NE FINISHED

How this triple was built (4 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: W4 | Statement: [W4 star-forming region, catalogDesignation, W4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: W4
Context triple: [W4 star-forming region, catalogDesignation, W4]
  • A. W6
    W6 is the IATA airline designator used to identify the low-cost carrier Wizz Air on tickets, timetables, and flight information systems.
  • B. W3
    W3 is a massive, active star-forming molecular cloud complex in the Perseus Arm of the Milky Way, known for hosting numerous young stellar objects and compact H II regions.
  • C. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • D. The W
    The W is the commonly used nickname for Mississippi University for Women, a public university in Columbus, Mississippi.
  • E. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: W4
Triple: [W4 star-forming region, catalogDesignation, W4]
Generated description
W4 is a prominent star-forming region in the Milky Way, notable for its large ionized gas bubble and active formation of massive young stars.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: W4
Target entity description: W4 is a prominent star-forming region in the Milky Way, notable for its large ionized gas bubble and active formation of massive young stars.
  • A. W6
    W6 is the IATA airline designator used to identify the low-cost carrier Wizz Air on tickets, timetables, and flight information systems.
  • B. W3
    W3 is a massive, active star-forming molecular cloud complex in the Perseus Arm of the Milky Way, known for hosting numerous young stellar objects and compact H II regions.
  • C. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • D. The W
    The W is the commonly used nickname for Mississippi University for Women, a public university in Columbus, Mississippi.
  • E. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • F. None of above. chosen

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_69bd4413f9908190afcff44d7929cc4c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ffc2ab08190992db2400562bcee completed March 20, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77a41ca08190a8fbfa405b15d68c completed March 21, 2026, 10:49 a.m.
NEDg Description generation batch_69be78292a988190ba51886095629b9c completed March 21, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_69be7892b34c819095100b14a80d6fa4 completed March 21, 2026, 10:53 a.m.
Created at: March 20, 2026, 1:30 p.m.