Triple
T12374649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Bath |
E295089
|
entity |
| Predicate | hasNearbyCityFunction |
P104638
|
FINISHED |
| Object | supports local maritime businesses |
—
|
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: supports local maritime businesses | Statement: [Port of Bath, hasNearbyCityFunction, supports local maritime businesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCityFunction Context triple: [Port of Bath, hasNearbyCityFunction, supports local maritime businesses]
-
A.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
B.
hasNearbyUSCity
Indicates that one location has at least one city in the United States situated within a specified nearby distance.
-
C.
hasNearbyMajorCityCountry
Indicates that an entity has a nearby major city located in the specified country.
-
D.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
E.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa8ca7c8190b3f8e9c2ec23e837 |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93fa244148190a960be3ff6f1cf45 |
completed | April 10, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:54 p.m.