Triple
T16743581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Job Training Partnership Act |
E406892
|
entity |
| Predicate | supersededBy |
P101
|
FINISHED |
| Object | WIA |
E928686
|
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: WIA | Statement: [Job Training Partnership Act, supersededBy, WIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WIA Context triple: [Job Training Partnership Act, supersededBy, WIA]
-
A.
WIA
WIA is a Microsoft Windows service and API that enables communication between the operating system and imaging hardware such as scanners and digital cameras.
-
B.
WIA
chosen
WIA is a U.S. federal law enacted in 1998 to improve workforce development by providing job training, employment services, and support for adults, dislocated workers, and youth.
-
C.
WICA
WICA is the ICAO airport code assigned to Kertajati International Airport in West Java, Indonesia.
-
D.
Wa
Wa is a town in northwestern Ghana that serves as an administrative, commercial, and cultural hub for the surrounding region.
-
E.
Wa
Wa is an ancient Chinese exonym historically used to refer to the people and early polities of the Japanese archipelago.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa205138819080284fd9a4341225 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d52d88081909695a08d00bd2257 |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:21 a.m.