Triple
T11639384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denali Star |
E276619
|
entity |
| Predicate | operatingMonthsApproximate |
P100126
|
FINISHED |
| Object | mid-May to mid-September |
—
|
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: mid-May to mid-September | Statement: [Denali Star, operatingMonthsApproximate, mid-May to mid-September]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingMonthsApproximate Context triple: [Denali Star, operatingMonthsApproximate, mid-May to mid-September]
-
A.
durationOfUse
Indicates the length of time for which something is used or remains in use.
-
B.
operatedSince
Indicates that an entity has been in operation continuously from a specified starting time or date.
-
C.
typicalUseDays
Indicates the usual or expected number of days over which something is used or intended to be used.
-
D.
durationInYears
Indicates the length of time associated with something, measured in whole or fractional years.
-
E.
banDurationApproximate
Indicates that the duration of a ban is known only approximately rather than as an exact, precise time period.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25e90c08190b7fb73939a2be3d7 |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
| PDg | Predicate description generation | batch_69d87f30642c8190ad94fa061cde186b |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:39 p.m.