Triple
T12761197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free Trade Area of the Americas |
E304997
|
entity |
| Predicate | wouldHaveIncluded |
P13998
|
FINISHED |
| Object | NAFTA members |
—
|
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: NAFTA members | Statement: [Free Trade Area of the Americas, wouldHaveIncluded, NAFTA members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wouldHaveIncluded Context triple: [Free Trade Area of the Americas, wouldHaveIncluded, NAFTA members]
-
A.
wouldHaveHadMembers
chosen
Indicates a hypothetical or counterfactual relationship in which an entity, under certain conditions or in an unrealized scenario, would have included specific members.
-
B.
formerlyIncluded
Indicates that an entity was previously part of, contained in, or a member of another entity, but is no longer included.
-
C.
wouldHaveHeldPosition
Indicates that an entity was expected or intended to occupy a particular role or office, but did not actually hold it in reality.
-
D.
wasIn
Indicates that an entity existed, occurred, or was located within a particular place or context during a specified time or situation.
-
E.
wasA
Indicates that an entity previously had a certain role, type, or classification in the past.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.