Triple
T21945835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Thompson as Gareth Peirce |
E541929
|
entity |
| Predicate | portrayalRegion |
P146643
|
FINISHED |
| Object | British cinema |
—
|
LITERAL 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: British cinema | Statement: [Emma Thompson as Gareth Peirce, portrayalRegion, British cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalRegion Context triple: [Emma Thompson as Gareth Peirce, portrayalRegion, British cinema]
-
A.
represented region
Indicates that one entity serves as a symbolic or formal depiction of a specific geographic or spatial area.
-
B.
placeRegion
Indicates that a place is located within, or is part of, a larger geographic or administrative region.
-
C.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
D.
mentionsRegion
Indicates that one entity explicitly refers to or cites a specific geographic region in its content or context.
-
E.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
- F. None of above. chosen
Provenance (4 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12427c2b48190949c41bd3be2d9f3 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb6991948190a428c3c3bfd1c3b8 |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:57 p.m.