Triple
T241878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weyerhaeuser Company |
E4947
|
entity |
| Predicate | tradedAs |
P2822
|
FINISHED |
| Object | WY |
E4947
|
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: WY | Statement: [Weyerhaeuser Company, tradedAs, WY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WY Context triple: [Weyerhaeuser Company, tradedAs, WY]
-
A.
WY
chosen
WY is the New York Stock Exchange ticker symbol for Weyerhaeuser Company, one of the world’s largest private owners of timberlands and a major forest products company.
-
B.
W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
-
C.
WR
WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
-
D.
W3
W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
-
E.
BW
BW is the common abbreviation for the Dutch Civil Code, the primary body of private law in the Netherlands.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25cee6f208190b996be4faa700910 |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36961e5688190b3a1ff61bb06233c |
completed | Feb. 28, 2026, 10:17 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.