Triple
T15217149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CUSIP |
E363664
|
entity |
| Predicate | hasFirstSixCharactersMeaning |
P27718
|
FINISHED |
| Object | issuer identifier |
—
|
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: issuer identifier | Statement: [CUSIP, hasFirstSixCharactersMeaning, issuer identifier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstSixCharactersMeaning Context triple: [CUSIP, hasFirstSixCharactersMeaning, issuer identifier]
-
A.
hasLastThreeLettersMeaning
Indicates that the last three letters of one entity (typically a word or string) together form a meaningful unit or have a specific semantic significance.
-
B.
hasPrefixMeaning
chosen
Indicates that one entity serves as a semantic prefix of another, contributing a specific meaning to the start of the second entity.
-
C.
hasInitialLetters
Indicates that one entity’s initial letters or acronym are derived from or correspond to the other entity.
-
D.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.