Triple
T309511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAS |
E6372
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | AAS |
E5037
|
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: AAS | Statement: [AAS, acronym, AAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AAS Context triple: [AAS, acronym, AAS]
-
A.
AAS
chosen
AAS is a major professional organization dedicated to the advancement of astronomy and related sciences in the United States.
-
B.
AAS
AAS is a pan-African scientific organization that promotes excellence in science, technology, and innovation to drive sustainable development across the African continent.
-
C.
AA
AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
-
D.
AAR
AAR is the American Association of Railroads' wheel arrangement classification system commonly used to describe locomotive axle configurations in North America.
-
E.
AIP
AIP is a leading U.S.-based professional organization that advances and disseminates knowledge in the physical sciences through research publications, education, and advocacy.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea33ba688190b30d285cd7aa0d82 |
completed | Feb. 28, 2026, 1:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3b47702cc81909c83e6770cb1e855 |
completed | March 1, 2026, 3:37 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.