Triple
T13410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Academy of Sciences |
E269
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | NAS |
E269
|
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: NAS | Statement: [National Academy of Sciences, shortName, NAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NAS Context triple: [National Academy of Sciences, shortName, NAS]
-
A.
NAS
chosen
NAS is a private, nonprofit society of distinguished scholars in the United States that advises the nation on matters related to science and technology.
-
B.
WAS
WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
-
C.
NMTI
NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
-
D.
NLS
NLS (oN-Line System) was an early, pioneering computer system that introduced many foundational concepts of modern computing, including the mouse, hypertext, and collaborative editing.
-
E.
Tymshare
Tymshare was an influential American time-sharing and computer services company active in the 1960s–1980s that helped pioneer remote computing and software services for businesses.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a240014418819090625e2fb774a2e6 |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a248e3cd308190be7f51f817d4e2b2 |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.