Triple

T36756173
Position Surface form Disambiguated ID Type / Status
Subject Splinter E908056 entity
Predicate hasAward P219 FINISHED
Object Best Makeup at Screamfest Horror Film Festival
Best Makeup at Screamfest Horror Film Festival is an award recognizing outstanding makeup effects in films showcased at the Screamfest Horror Film Festival.
E2197294 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: Best Makeup at Screamfest Horror Film Festival | Statement: [Splinter, hasAward, Best Makeup at Screamfest Horror Film Festival]
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: Best Makeup at Screamfest Horror Film Festival
Triple: [Splinter, hasAward, Best Makeup at Screamfest Horror Film Festival]
Generated description
Best Makeup at Screamfest Horror Film Festival is an award recognizing outstanding makeup effects in films showcased at the Screamfest Horror Film Festival.

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_69f76e779bec8190be0e1f87a131e0f4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c97831f08190a2eda81dc6fce83b completed May 3, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c173af6308190a5c5bad4306fecfb completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c193a1fc881908332ab00462372e1 completed June 24, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_6a3c57b8bd4c81909d429a799dac9063 completed June 24, 2026, 10:18 p.m.
Created at: May 3, 2026, 4:12 p.m.