Triple
T31942813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lago de Cidra |
E815570
|
entity |
| Predicate | hasShorelineMunicipality |
P180359
|
FINISHED |
| Object | Cidra |
—
|
NE NERFINISHED |
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: Cidra | Statement: [Lago de Cidra, hasShorelineMunicipality, Cidra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShorelineMunicipality Context triple: [Lago de Cidra, hasShorelineMunicipality, Cidra]
-
A.
hasCoastalMunicipalities
Indicates that a region or higher-level area includes one or more municipalities that are located along a sea or ocean coastline.
-
B.
hasShorelineCountry
Indicates that a country possesses a coastline or land boundary directly adjacent to a particular body of water or coastal region.
-
C.
hasLongShoreline
Indicates that an entity possesses an extensive or unusually long shoreline relative to typical cases.
-
D.
hasShorelineUse
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
E.
hasCoastalMunicipalitiesNeighbor
Indicates that one coastal municipality directly borders or adjoins another coastal municipality.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
| PDg | Predicate description generation | batch_69f73adfd9a081908adae6bd59dfefb9 |
completed | May 3, 2026, 12:09 p.m. |
Created at: May 1, 2026, 12:06 a.m.