Triple
T3859451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Act to Promote the Defense of the United States |
E90097
|
entity |
| Predicate | regionOfEffect |
P1586
|
FINISHED |
| Object | Allied countries worldwide |
—
|
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: Allied countries worldwide | Statement: [An Act to Promote the Defense of the United States, regionOfEffect, Allied countries worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfEffect Context triple: [An Act to Promote the Defense of the United States, regionOfEffect, Allied countries worldwide]
-
A.
placeOfEffect
Indicates the location or setting where an action, event, or effect takes place or is realized.
-
B.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
C.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
D.
regionExposure
Indicates that an entity is subject to or affected by exposure within a specific geographic or spatial region.
-
E.
realmWithin
Indicates that one realm or domain is contained inside, or exists as a subset of, another realm or domain.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1ff39c8190b83a88abd840a0e3 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.