Triple
T34343309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afon Lloer |
E881357
|
entity |
| Predicate | AfonMeaning |
P74345
|
FINISHED |
| Object | river |
—
|
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: river | Statement: [Afon Lloer, AfonMeaning, river]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AfonMeaning Context triple: [Afon Lloer, AfonMeaning, river]
-
A.
waterfallNameEtymology
Indicates the origin or reasoning behind the name given to a particular waterfall.
-
B.
toponymLiteralMeaning
chosen
Indicates the literal or etymological meaning of a place name (toponym), describing what the name directly translates to or signifies.
-
C.
reservoirNameEtymology
Indicates the origin or source of a reservoir’s name, such as the historical, cultural, or linguistic reason it was given that name.
-
D.
watercourseName
Indicates the name assigned to a river, stream, or other flowing body of water in the relationship.
-
E.
featuresRiverPersonifications
Indicates that something includes or depicts personified representations of rivers as characters or agents.
- 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_69f349bc55e881908c8e338ef76b0043 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:58 a.m.