Triple
T5577004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AML |
E146343
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | AML |
E146343
|
NE 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: AML | Statement: [AML, hasAbbreviation, AML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AML Context triple: [AML, hasAbbreviation, AML]
-
A.
AML
chosen
AML is the commonly used abbreviation for the Mexican Academy of Language, a scholarly institution dedicated to the study and regulation of the Spanish language in Mexico.
-
B.
AMA
AMA is the leading professional association and lobbying group representing physicians and medical students in the United States.
-
C.
ARN
ARN is the three-letter IATA airport code for Stockholm Arlanda Airport, the main international gateway to Stockholm and one of Sweden’s busiest airports.
-
D.
AMF
AMF is a regional Arab financial institution that promotes monetary cooperation, economic integration, and development among its member states.
-
E.
AMF
AMF is a core 5G network function responsible for managing user access, registration, mobility, and connection handling between devices and the mobile network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020697fbc8190bd084d7896db3ab8 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02855acac8190bd00219aa9647e98 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:37 p.m.