Triple
T4553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turing Award |
E88
|
entity |
| Predicate | monetaryValue |
P482
|
FINISHED |
| Object | 1000000 USD |
—
|
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: 1000000 USD | Statement: [Turing Award, monetaryValue, 1000000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monetaryValue Context triple: [Turing Award, monetaryValue, 1000000 USD]
-
A.
currency
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
B.
endowmentCurrency
Indicates the type of currency in which an endowment is denominated or valued.
-
C.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
D.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
E.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23c24b3d08190a714126292fd5479 |
completed | Feb. 28, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69a23998af288190855f0456740cbd51 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23c23fef88190ba5d6d86acd4a66f |
completed | Feb. 28, 2026, 12:51 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.