Triple
T7541354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treasury bonds |
E178281
|
entity |
| Predicate | hasCouponType |
P77230
|
FINISHED |
| Object | fixed rate |
—
|
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: fixed rate | Statement: [Treasury bonds, hasCouponType, fixed rate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCouponType Context triple: [Treasury bonds, hasCouponType, fixed rate]
-
A.
couponType
chosen
Indicates the specific category or kind of coupon associated with an offer or transaction.
-
B.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
C.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
D.
hasPromotionFrom
Indicates that an entity receives or is associated with a promotion that originates from a specified source entity (such as a campaign, organization, or person).
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d8eedc81908c1ae421e0e63798 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.