Triple
T22670856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Mahón |
E559912
|
entity |
| Predicate | hasInletWidth |
P3989
|
FINISHED |
| Object | narrow entrance from the Mediterranean Sea |
—
|
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: narrow entrance from the Mediterranean Sea | Statement: [Port of Mahón, hasInletWidth, narrow entrance from the Mediterranean Sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInletWidth Context triple: [Port of Mahón, hasInletWidth, narrow entrance from the Mediterranean Sea]
-
A.
hasInlet
Indicates that one entity serves as an inlet or entry point through which another entity receives a flow of material, energy, or fluid.
-
B.
hasWidth
chosen
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
C.
hasChamberWidth
Indicates that an entity possesses a chamber whose width has a specified value or range.
-
D.
hasNarrowestWidth
Indicates that one entity has the smallest width dimension compared to a specified set of entities or alternatives.
-
E.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781f946c8190add74a7dac2b1819 |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:10 p.m.