Triple
T15200981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freycinet gauge |
E363265
|
entity |
| Predicate | standardLoadedDraught_m |
P36729
|
FINISHED |
| Object | 1.8 |
—
|
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: 1.8 | Statement: [Freycinet gauge, standardLoadedDraught_m, 1.8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardLoadedDraught_m Context triple: [Freycinet gauge, standardLoadedDraught_m, 1.8]
-
A.
draught
Indicates that one entity is the version or serving of a beverage (typically beer) that is drawn from a cask, keg, or tap rather than from a bottle or can.
-
B.
hasDraught
Indicates that an entity has a specific vertical distance between the waterline and the lowest point of its hull or structure (its draught).
-
C.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
-
D.
standardDisplacement
Indicates the typical or officially specified amount of displacement (such as volume, weight, or capacity) associated with an entity under standard conditions.
-
E.
shipDraft
chosen
Indicates the depth of a ship’s hull below the waterline, typically representing how deeply the vessel sits in the water.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b588b88190a88e91d521acbdfe |
completed | April 15, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:10 a.m.