Triple
T22233054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Denia |
E549516
|
entity |
| Predicate | hasApproximateSailingTimeToIbiza |
P146840
|
FINISHED |
| Object | 2 to 3 hours |
—
|
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: 2 to 3 hours | Statement: [Port of Denia, hasApproximateSailingTimeToIbiza, 2 to 3 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateSailingTimeToIbiza Context triple: [Port of Denia, hasApproximateSailingTimeToIbiza, 2 to 3 hours]
-
A.
distanceToIbiza
Indicates the spatial distance between a given entity’s location and the location of Ibiza.
-
B.
dateToReachMediterranean
Indicates the date on which an entity is expected or scheduled to arrive at, or first reach, the Mediterranean.
-
C.
distanceToBerlengas
Indicates the measured distance between a given entity’s location and the Berlengas.
-
D.
hasApproximateDirectionFromCasablanca
Indicates that one entity is located in a direction that is only roughly or loosely specified relative to Casablanca.
-
E.
hasNearbyHarbor
Indicates that one location has a harbor situated close to it in geographic proximity.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf4e0348190b755a9ac0bc96cdd |
completed | April 28, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
| PDg | Predicate description generation | batch_69e7222e74248190a2d3671049f117f2 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:38 p.m.