Triple
T11560463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel S. Wilks Memorial Award |
E274127
|
entity |
| Predicate | associatedOrganization |
P37
|
FINISHED |
| Object | ASA |
E728770
|
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: ASA | Statement: [Samuel S. Wilks Memorial Award, associatedOrganization, ASA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ASA Context triple: [Samuel S. Wilks Memorial Award, associatedOrganization, ASA]
-
A.
ASA
ASA is the commonly used abbreviation for the Academy of Sciences of Albania, the country’s leading scientific research and advisory institution.
-
B.
ASA
chosen
ASA is the leading professional organization in the United States dedicated to advancing the practice and profession of statistics.
-
C.
ASA
ASA is an abbreviation commonly used to refer to the Assistant Secretary of the Army, a senior civilian official in the United States Department of the Army responsible for high-level policy and oversight.
-
D.
ASA
ASA is the ICAO airline designator used to identify Alaska Airlines in international aviation operations and communications.
-
E.
ASA
ASA is the acronym for Aeropuertos y Servicios Auxiliares, the Mexican government agency responsible for operating and managing numerous airports and providing auxiliary aviation services in Mexico.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a899d4481909a3bce3147763b51 |
completed | April 10, 2026, 5:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e88b84d48190948243646bb5fd2b |
completed | April 21, 2026, 3:01 a.m. |
Created at: April 8, 2026, 9:37 p.m.