Triple
T7628577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kia Motors manufacturing plant (West Point, Georgia) |
E172699
|
entity |
| Predicate | investmentAmount |
P482
|
FINISHED |
| Object | over US$1 billion |
—
|
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: over US$1 billion | Statement: [Kia Motors manufacturing plant (West Point, Georgia), investmentAmount, over US$1 billion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: investmentAmount Context triple: [Kia Motors manufacturing plant (West Point, Georgia), investmentAmount, over US$1 billion]
-
A.
owedMoneyTo
Indicates that one entity has a financial obligation or debt that must be paid to another entity.
-
B.
paymentAmount
Indicates the specific monetary value involved in a payment transaction between parties.
-
C.
investmentType
Indicates the specific category or nature of an investment associated with an entity or transaction.
-
D.
typicalInvestmentSize
Indicates the usual or most common amount of money invested in a single investment or deal.
-
E.
monetaryValue
chosen
Indicates the amount of money associated with an entity, event, or transaction.
- 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:56 p.m.