Triple
T3680424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M/V Kennicott |
E78096
|
entity |
| Predicate | canTransport |
P2059
|
FINISHED |
| Object | walk-on passengers |
—
|
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: walk-on passengers | Statement: [M/V Kennicott, canTransport, walk-on passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canTransport Context triple: [M/V Kennicott, canTransport, walk-on passengers]
-
A.
usesTransport
Indicates that an entity employs or relies on a particular mode or means of transportation to move from one place to another.
-
B.
transports
chosen
Indicates that one entity carries or conveys another entity from one place to another.
-
C.
airTransportableBy
Indicates that something can be transported or carried by air using a specific aircraft or air transport method.
-
D.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
E.
transportAssumption
Indicates an assumption that something can be transported or carried from one place or context to another.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc49153ec81909ff3a3df54416d0e |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.