Triple
T20016878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caen Hill Locks |
E494744
|
entity |
| Predicate | numberOfLocksInMainFlight |
P138387
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Caen Hill Locks, numberOfLocksInMainFlight, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLocksInMainFlight Context triple: [Caen Hill Locks, numberOfLocksInMainFlight, 16]
-
A.
numberOfGates
Indicates the quantity of gates associated with or belonging to an entity.
-
B.
hasLockFlight
Indicates that one entity is associated with a specific lock flight, representing a relationship where the entity uses, contains, or is located at that sequence of canal locks.
-
C.
numberOfCaptiveFlights
Indicates the number of flights during which an entity is held or transported in captivity.
-
D.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
-
E.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623cb8188190b95913ffed895930 |
completed | April 20, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:34 p.m.