Triple
T1422575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guernsey pound |
E30256
|
entity |
| Predicate | valueRelation |
P28911
|
FINISHED |
| Object | 1 Guernsey pound = 1 pound sterling |
—
|
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: 1 Guernsey pound = 1 pound sterling | Statement: [Guernsey pound, valueRelation, 1 Guernsey pound = 1 pound sterling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: valueRelation Context triple: [Guernsey pound, valueRelation, 1 Guernsey pound = 1 pound sterling]
-
A.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
B.
titleRelation
Indicates a relationship where one entity serves as the title, designation, or formal name associated with another entity.
-
C.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
D.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
multipleRelation
Indicates that an entity is involved in more than one distinct relationship of the specified type with other entities.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69a4c52bbb748190aaa804438d31f4c2 |
completed | March 1, 2026, 11 p.m. |
Created at: March 1, 2026, 8 p.m.