Triple
T7130697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Sanitary Fair |
E166177
|
entity |
| Predicate | raisedMoneyFor |
P75025
|
FINISHED |
| Object | Union Army medical services |
—
|
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: Union Army medical services | Statement: [Metropolitan Sanitary Fair, raisedMoneyFor, Union Army medical services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raisedMoneyFor Context triple: [Metropolitan Sanitary Fair, raisedMoneyFor, Union Army medical services]
-
A.
owedMoneyTo
Indicates that one entity has a financial obligation or debt that must be paid to another entity.
-
B.
seeksFundingFrom
Indicates that one entity is actively trying to obtain financial support or investment from another entity.
-
C.
raisedWith
Indicates that two or more entities grew up together in the same household or close environment during their formative years.
-
D.
fundingLevel
Indicates the amount or degree of financial resources allocated or committed to an entity, project, or activity.
-
E.
raisesCapitalFrom
Indicates that one entity obtains funding or financial resources from another 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66dc2388190bdec018f1cc6b20a |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:44 p.m.