Triple
T318594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panama Canal |
E7762
|
entity |
| Predicate | maximumShipClass |
P2429
|
FINISHED |
| Object | Panamax |
—
|
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: Panamax | Statement: [Panama Canal, maximumShipClass, Panamax]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumShipClass Context triple: [Panama Canal, maximumShipClass, Panamax]
-
A.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
B.
maximumVesselType
chosen
Indicates the highest or largest class, size, or category of vessel that is allowed, applicable, or associated in a given context.
-
C.
originalShipType
Indicates the type or category of ship that an entity was originally classified or built as.
-
D.
notableShip
Indicates that there is a notable or significant ship associated with the subject entity.
-
E.
standardDisplacement
Indicates the typical or officially specified amount of displacement (such as volume, weight, or capacity) associated with an entity under standard conditions.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.