Triple
T2216766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristin Scott Thomas as Katherine Clifton |
E48049
|
entity |
| Predicate | filmRuntimeApprox |
P36872
|
FINISHED |
| Object | 162 minutes |
—
|
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: 162 minutes | Statement: [Kristin Scott Thomas as Katherine Clifton, filmRuntimeApprox, 162 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmRuntimeApprox Context triple: [Kristin Scott Thomas as Katherine Clifton, filmRuntimeApprox, 162 minutes]
-
A.
filmGauge
Indicates the specific width or size of the film stock used in a motion picture or photographic recording.
-
B.
storyTimeSpanInFilm
Indicates the duration of time that the story or narrative covers within the film.
-
C.
hasEpisodeRuntime
Indicates the duration of time that each individual episode of a series or show runs.
-
D.
MPADuration
Indicates the length of time associated with a specific MPA (Marine Protected Area) or MPA-related event or status.
-
E.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc00f4c3881909d03301fcdfa8b67 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdaa26d48190860c33fd464c4845 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf0c2b8881908553eed5be17a9c2 |
completed | March 7, 2026, 6 a.m. |
Created at: March 4, 2026, 7:46 p.m.