Triple

T33895964
Position Surface form Disambiguated ID Type / Status
Subject Laura Bailey E868910 entity
Predicate awardReceived P11 FINISHED
Object The Game Awards for Best Performance
The Game Awards for Best Performance is an annual honor presented at The Game Awards ceremony recognizing an individual actor’s outstanding performance in a video game.
E1984355 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: The Game Awards for Best Performance | Statement: [Laura Bailey, awardReceived, The Game Awards for Best Performance]
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: The Game Awards for Best Performance
Triple: [Laura Bailey, awardReceived, The Game Awards for Best Performance]
Generated description
The Game Awards for Best Performance is an annual honor presented at The Game Awards ceremony recognizing an individual actor’s outstanding performance in a video game.

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_69f34997703c8190866b1d404bce531f completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7017f668c81909728d5db01e77d10 completed May 3, 2026, 8:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36823e736481908aef1d6187062cf3 completed June 20, 2026, 12:06 p.m.
NEDg Description generation batch_6a3683b5ac0881909f03e1e94896067d completed June 20, 2026, 12:12 p.m.
NED2 Entity disambiguation (via description) batch_6a36848c2cd88190b28d40551392741b completed June 20, 2026, 12:16 p.m.
Created at: May 1, 2026, 1:48 a.m.