Triple

T26222756
Position Surface form Disambiguated ID Type / Status
Subject 944th Fighter Wing E655806 entity
Predicate hasDetachment P29892 FINISHED
Object Detachment 3, 944th Fighter Wing
Detachment 3, 944th Fighter Wing is a subordinate Air Force Reserve unit that supports the 944th Fighter Wing’s operational and training missions.
E1721116 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: Detachment 3, 944th Fighter Wing | Statement: [944th Fighter Wing, hasDetachment, Detachment 3, 944th 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: Detachment 3, 944th Fighter Wing
Triple: [944th Fighter Wing, hasDetachment, Detachment 3, 944th Fighter Wing]
Generated description
Detachment 3, 944th Fighter Wing is a subordinate Air Force Reserve unit that supports the 944th Fighter Wing’s operational and training 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_69ee5b4a77e08190bfcb5f8ecdc55abd completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d5127d48190b28c89797f2852f2 completed May 2, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a119a45a960819083e66a01ca05c074 completed May 23, 2026, 12:15 p.m.
NEDg Description generation batch_6a119b1444008190a4cdcbe5fd8bca98 completed May 23, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a119c2d13388190869495b5b068ab15 completed May 23, 2026, 12:23 p.m.
Created at: April 26, 2026, 8:56 p.m.