Triple
T13379543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans Ditlev Bendixsen |
E319276
|
entity |
| Predicate | vesselMaterialSpecializedIn |
P90707
|
FINISHED |
| Object | wooden hulls |
—
|
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: wooden hulls | Statement: [Hans Ditlev Bendixsen, vesselMaterialSpecializedIn, wooden hulls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vesselMaterialSpecializedIn Context triple: [Hans Ditlev Bendixsen, vesselMaterialSpecializedIn, wooden hulls]
-
A.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
B.
boatConstructionMaterial
chosen
Indicates the material from which a boat is (or was) constructed.
-
C.
featuresVessel
Indicates that one entity includes, presents, or prominently displays a particular vessel as part of its composition, content, or configuration.
-
D.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
E.
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.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce56c6c8190adf4e19f6d1bc233 |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.