Triple
T46553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester Ship Canal |
E912
|
entity |
| Predicate | maximumVesselType |
P2429
|
FINISHED |
| Object | ocean‑going ships |
—
|
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: ocean‑going ships | Statement: [Manchester Ship Canal, maximumVesselType, ocean‑going ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumVesselType Context triple: [Manchester Ship Canal, maximumVesselType, ocean‑going ships]
-
A.
maximumTrunkDiameter
Indicates the largest thickness of a trunk measured across its widest point.
-
B.
maxSpeed
Indicates the greatest possible speed at which an entity can move or operate under specified conditions.
-
C.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
D.
maximumService
Indicates that an entity provides the highest allowable or achievable level of service within a given context or system.
-
E.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
- F. None of above. chosen
Provenance (4 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b1bf2c081908f20e13939b713ff |
completed | Feb. 28, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69a24abd07508190a83ffba5368c1c79 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b1a42888190b56a5e457e11604f |
completed | Feb. 28, 2026, 1:55 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.