Triple
T9902252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anderton Boat Lift |
E182312
|
entity |
| Predicate | caissonCapacity |
P80385
|
FINISHED |
| Object | one narrowboat |
—
|
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: one narrowboat | Statement: [Anderton Boat Lift, caissonCapacity, one narrowboat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caissonCapacity Context triple: [Anderton Boat Lift, caissonCapacity, one narrowboat]
-
A.
hasCraneCapacity
Indicates that an entity possesses a crane with a specified lifting capacity or load-handling capability.
-
B.
hasTwinCaissons
Indicates that something is equipped with or associated with a pair of caissons functioning together as twins.
-
C.
unitCapacity
chosen
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
D.
missionBayCapacity
Indicates the capacity or maximum volume that Mission Bay can hold or accommodate.
-
E.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4e391888190a3f5e5a1bf1cf9ff |
completed | April 2, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69cd1d8c584081908b73de75eb18e438 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:40 p.m.