Triple
T594316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurodollar futures |
E17345
|
entity |
| Predicate | tickSize |
P16094
|
FINISHED |
| Object | 0.005 price points |
—
|
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: 0.005 price points | Statement: [Eurodollar futures, tickSize, 0.005 price points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tickSize Context triple: [Eurodollar futures, tickSize, 0.005 price points]
-
A.
grainSize
Indicates the relative coarseness or fineness of the material or particles involved in the relationship.
-
B.
hasLotSize
Indicates that an entity possesses a specific amount or extent of physical area, typically referring to the size of a parcel of land or property lot.
-
C.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
D.
fieldSize
Indicates the magnitude or dimensions of a field associated with an entity or context.
-
E.
tickerFor
Indicates that one entity is the stock ticker symbol used to uniquely identify another entity (typically a publicly traded company or security) in financial markets.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd15c5881909b59ed4c88687e7b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494ceeb7881909a91ed1a35d5bf0a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985ada988190aaea628a9b55bca4 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.