Triple
T3461304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AK |
E73029
|
entity |
| Predicate | hasNotableUnit |
P1198
|
FINISHED |
| Object | Kedyw |
E106076
|
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: Kedyw | Statement: [AK, hasNotableUnit, Kedyw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kedyw Context triple: [AK, hasNotableUnit, Kedyw]
-
A.
Kedyw
chosen
Kedyw was a special operations and sabotage unit of the Polish underground Home Army that carried out resistance actions against Nazi German occupation during World War II.
-
B.
Kabiye
Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
-
C.
Wyoma
Wyoma is a residential neighborhood located within the city of Lynn in northeastern Massachusetts.
-
D.
Kibibi
Kibibi is a lively and energetic host character in Disney's "Festival of the Lion King" stage show at Disney theme parks.
-
E.
Owaneco
Owaneco was a prominent Mohegan sachem (chief) known for his leadership and land dealings in colonial New England during the late 17th and early 18th centuries.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae745e081909007cd3a664c57f3 |
completed | March 8, 2026, 6:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3611ff950819081b49f5c75aa6e4d |
completed | March 13, 2026, 12:58 a.m. |
Created at: March 8, 2026, 3:17 p.m.