Triple
T26611741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tynemouth Lighthouse |
E667940
|
entity |
| Predicate | usedByVessels |
P11945
|
FINISHED |
| Object | commercial shipping |
—
|
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: commercial shipping | Statement: [Tynemouth Lighthouse, usedByVessels, commercial shipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByVessels Context triple: [Tynemouth Lighthouse, usedByVessels, commercial shipping]
-
A.
usesVesselsOperatedBy
Indicates that one entity makes use of vessels that are operated or controlled by another entity.
-
B.
usesVesselType
chosen
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
namedVesselOf
Indicates that one entity is the specific named vessel (e.g., ship, boat, or craft) associated with or belonging to another entity.
-
D.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
E.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
- 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_69ee9cfe16088190a3dddd68e3c7b1ea |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 27, 2026, 2:17 a.m.