Triple

T34841097
Position Surface form Disambiguated ID Type / Status
Subject Louisiana Air National Guard E1004341 entity
Predicate hasMajorUnit P15759 FINISHED
Object 159th Fighter Wing
The 159th Fighter Wing is a primary combat aviation unit of the Louisiana Air National Guard, responsible for providing trained and equipped fighter forces for both state and federal missions.
E2170098 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: 159th Fighter Wing | Statement: [Louisiana Air National Guard, hasMajorUnit, 159th Fighter Wing]
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: 159th Fighter Wing
Triple: [Louisiana Air National Guard, hasMajorUnit, 159th Fighter Wing]
Generated description
The 159th Fighter Wing is a primary combat aviation unit of the Louisiana Air National Guard, responsible for providing trained and equipped fighter forces for both state and federal missions.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7812ef82c819085c6119c2272fb7d completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38dde459408190b102185449d10a35 completed June 22, 2026, 7:01 a.m.
NEDg Description generation batch_6a38f3daf5188190921d7e7cf19fd18a completed June 22, 2026, 8:35 a.m.
NED2 Entity disambiguation (via description) batch_6a38f513d3e88190aa25e33d93bf12a4 completed June 22, 2026, 8:40 a.m.
Created at: May 3, 2026, 4 p.m.