Triple
T22769537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GAFTA |
E563216
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | GAFTA |
—
|
NE NERFINISHED |
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: GAFTA | Statement: [GAFTA, shortName, GAFTA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GAFTA Context triple: [GAFTA, shortName, GAFTA]
-
A.
GAFTA
chosen
GAFTA is a regional free trade agreement among Arab League member states aimed at eliminating trade barriers and promoting economic integration in the Arab world.
-
B.
SAFTA
SAFTA is a regional free trade agreement among South Asian countries aimed at reducing tariffs and promoting economic integration within the SAARC region.
-
C.
FTAA
FTAA is a proposed agreement to create a large free trade zone encompassing all countries in the Americas except Cuba.
-
D.
MCFTA
MCFTA is a multidisciplinary cultural complex in Midland, Michigan, offering theater, art exhibitions, music performances, and educational programs.
-
E.
FTA
FTA is a U.S. government agency within the Department of Transportation that provides financial and technical assistance for public transportation systems nationwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b59c9cc8190a6edd68f3209a672 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:27 p.m.