Triple
T2466914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valmur |
E55271
|
entity |
| Predicate | agingVessel |
P11978
|
FINISHED |
| Object | stainless steel tanks (common) |
—
|
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: stainless steel tanks (common) | Statement: [Valmur, agingVessel, stainless steel tanks (common)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingVessel Context triple: [Valmur, agingVessel, stainless steel tanks (common)]
-
A.
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.
-
B.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
E.
operatesVessel
Indicates that an agent is responsible for controlling, managing, or running the operation of a vessel.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.