Triple
T7460820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OCTO |
E176243
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | OCTO |
E176243
|
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: OCTO | Statement: [OCTO, acronym, OCTO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OCTO Context triple: [OCTO, acronym, OCTO]
-
A.
OCTO
chosen
OCTO is the District of Columbia’s Office of the Chief Technology Officer, the city government agency responsible for managing and advancing DC’s information technology and digital services.
-
B.
OCTAE
OCTAE is a U.S. Department of Education office that oversees federal programs and policy for career and technical education, adult education, and related workforce development initiatives.
-
C.
Oktoechos
Oktoechos is a liturgical system of eight musical modes used in Eastern Christian chant traditions.
-
D.
Octon
Octon is a small rural commune in southern France’s Hérault department, known for its proximity to the scenic Lac du Salagou and surrounding volcanic landscapes.
-
E.
Oktyabrsk
Oktyabrsk is a small industrial city in Russia located on the Volga River within Samara Oblast.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d525708190b7838e07ac2fbe1f |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8345f629c8190889081e18bdfe6f7 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:38 p.m.