Triple
T34646677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raħal Ġdid |
E889713
|
entity |
| Predicate | hasNearbyPortArea |
P64085
|
FINISHED |
| Object | Grand Harbour region |
—
|
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: Grand Harbour region | Statement: [Raħal Ġdid, hasNearbyPortArea, Grand Harbour region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyPortArea Context triple: [Raħal Ġdid, hasNearbyPortArea, Grand Harbour region]
-
A.
hasPortArea
chosen
Indicates that an entity possesses or is associated with a specific port area, typically representing the spatial extent or boundary of its port facilities.
-
B.
hasNearbyPortAccess
Indicates that an entity is located close enough to a port to feasibly use it for access or transport.
-
C.
hasNearbyPortionOf
Indicates that one entity has a portion that is spatially close to, but not necessarily touching, another entity or region.
-
D.
hasNearbyPortCountry
Indicates that one entity is a country that has a seaport located geographically close to the other entity.
-
E.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
- 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_69f349d825c88190bfc6170ac9281260 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffe6e2eb688190a45fd2c6415cd86a |
completed | May 10, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69ffe65939488190a35b9c2e9c7ad868 |
completed | May 10, 2026, 1:58 a.m. |
Created at: May 1, 2026, 2:04 a.m.