Triple

T35890067
Position Surface form Disambiguated ID Type / Status
Subject The Paint Hall E1037755 entity
Predicate alsoKnownAs P39 FINISHED
Object The Paint Hall Studios
The Paint Hall Studios is a major film and television production facility in Belfast, Northern Ireland, best known for hosting large-scale international productions such as HBO’s Game of Thrones.
 E2159192 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 Paint Hall Studios | Statement: [The Paint Hall, alsoKnownAs, The Paint Hall Studios]
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 Paint Hall Studios
Triple: [The Paint Hall, alsoKnownAs, The Paint Hall Studios]
Generated description
The Paint Hall Studios is a major film and television production facility in Belfast, Northern Ireland, best known for hosting large-scale international productions such as HBO’s Game of Thrones.

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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa3951e08190ac553bf8b0c2e7bd completed May 3, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4fc7efc8190900d279c9f5cfaff completed June 22, 2026, 2:59 a.m.
NEDg Description generation batch_6a38a5abc604819084de021a2c2262a3 completed June 22, 2026, 3:02 a.m.
NED2 Entity disambiguation (via description) batch_6a38a641d5988190b883de196f98fc71 completed June 22, 2026, 3:04 a.m.
Created at: May 3, 2026, 4:06 p.m.