Triple
T216235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gaucho |
E4110
|
entity |
| Predicate | hasRuntimeApprox |
P4874
|
FINISHED |
| Object | 115 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: 115 minutes | Statement: [The Gaucho, hasRuntimeApprox, 115 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuntimeApprox Context triple: [The Gaucho, hasRuntimeApprox, 115 minutes]
-
A.
hasApproximateDuration
chosen
Indicates that one entity has a duration that is estimated or not exact, typically expressed as an approximate length of time.
-
B.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
-
C.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
D.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
E.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.