Triple
T11649891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bluestones |
E276873
|
entity |
| Predicate | transportModeHypotheses |
P1379
|
FINISHED |
| Object | overland hauling |
—
|
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: overland hauling | Statement: [bluestones, transportModeHypotheses, overland hauling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeHypotheses Context triple: [bluestones, transportModeHypotheses, overland hauling]
-
A.
transportModePresent
Indicates that a particular mode of transportation is involved or available in the described context or event.
-
B.
transportAssumption
Indicates an assumption that something can be transported or carried from one place or context to another.
-
C.
transportModeImportant
Indicates that the mode of transport used is considered significant or plays an important role in the context of the relationship or action.
-
D.
transportModeFamily
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
-
E.
transportType
chosen
Indicates the mode or means of transportation used in carrying something or someone from one place 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cea9308190a13f7dd995ea07a4 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.