Triple
T6338053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wda |
E142540
|
entity |
| Predicate | hasPolishName |
P15778
|
FINISHED |
| Object | Wda |
E142540
|
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: Wda | Statement: [Wda, hasPolishName, Wda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wda Context triple: [Wda, hasPolishName, Wda]
-
A.
Wda
chosen
Wda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic, forested course and popularity for kayaking and canoeing.
-
B.
DWA
DWA is the commonly used abbreviation for the International Labour Organization’s Decent Work Agenda, a global framework promoting fair, secure, and dignified employment.
-
C.
WD
WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
-
D.
WD
WD is the National Rail station code for Woodside railway station in London, England.
-
E.
WHD
WHD is the U.S. Department of Labor’s Wage and Hour Division, the federal agency responsible for enforcing minimum wage, overtime pay, child labor, and other key labor standards.
- 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654e11988190b708426d3003716a |
completed | March 22, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604307b388190bbc59f5f57cb4bbe |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.