Triple
T19083438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reiki |
E467084
|
entity |
| Predicate | hasTypicalSessionDuration |
P109104
|
FINISHED |
| Object | 30–90 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: 30–90 minutes | Statement: [Reiki, hasTypicalSessionDuration, 30–90 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSessionDuration Context triple: [Reiki, hasTypicalSessionDuration, 30–90 minutes]
-
A.
hasTypicalVisitDuration
Indicates the usual or expected length of time that a visit to something typically lasts.
-
B.
hasTypicalPerformanceDuration
chosen
Indicates the usual or expected length of time that a performance or activity typically lasts.
-
C.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
-
D.
hasTypicalUseTime
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
-
E.
hasScreenTimeIn
Indicates that an entity appears on screen for a certain duration within a specified audiovisual work or segment.
- F. None of above.
Provenance (3 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2eab58c8190a987c88d633c92ec |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b9a604308190a3235184f9f2c056 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.