Triple
T4561361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United War Work Campaign |
E121797
|
entity |
| Predicate | targetedBeneficiaries |
P1806
|
FINISHED |
| Object | American soldiers |
—
|
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: American soldiers | Statement: [United War Work Campaign, targetedBeneficiaries, American soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetedBeneficiaries Context triple: [United War Work Campaign, targetedBeneficiaries, American soldiers]
-
A.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
B.
primaryBeneficiaries
chosen
Indicates which entities are the main recipients or advantaged parties resulting from a particular action, resource, or arrangement.
-
C.
philanthropicBeneficiary
Indicates that one entity is the recipient or target of another entity’s philanthropic giving or charitable support.
-
D.
sectorBenefited
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
-
E.
benefitedCountry
Indicates that one country gains an advantage, profit, or positive outcome from an action, event, or entity associated with another.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd582d98fc8190a760dbb5f20c775d |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.