Triple
T20615021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 10962 |
E506543
|
entity |
| Predicate | remainingCharactersRepresent |
P140789
|
FINISHED |
| Object | Attributes of the financial instrument |
—
|
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: Attributes of the financial instrument | Statement: [ISO 10962, remainingCharactersRepresent, Attributes of the financial instrument]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remainingCharactersRepresent Context triple: [ISO 10962, remainingCharactersRepresent, Attributes of the financial instrument]
-
A.
representsForCharacters
Indicates that one entity performs a representation or advocacy role on behalf of specific characters.
-
B.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
C.
characterRepresentation
Indicates a relationship where one entity serves as the symbolic, visual, or conceptual depiction of another entity’s character or identity.
-
D.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
-
E.
usesCharactersAs
Indicates that one entity employs or incorporates specific characters (such as letters, symbols, or glyphs) from another entity for its representation or functioning.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aadaf47881909e93efb535c6c1e3 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:41 a.m.