Triple
T1621725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant Wood |
E35045
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wood |
E109794
|
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: Wood | Statement: [Grant Wood, familyName, Wood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wood Context triple: [Grant Wood, familyName, Wood]
-
A.
Wood
chosen
Wood is a common English surname with historical roots in Britain, often originally referring to someone who lived or worked near a forest.
-
B.
Clinch Leatherwood
Clinch Leatherwood is the ruthless outlaw gunslinger who serves as the main antagonist in the comedy Western film "A Million Ways to Die in the West."
-
C.
Lignum vitae
Lignum vitae is a dense, extremely hard tropical hardwood tree native to the Caribbean, renowned for its durable wood and medicinal resin.
-
D.
Douglas fir
Douglas fir is a large, long-lived conifer native to western North America, valued for its strong timber and ecological importance in mountain and coastal forests.
-
E.
USOAK
USOAK is the UN/LOCODE identifier for the Port of Oakland, a major container shipping hub on the U.S. West Coast.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909b1fc788190b38c0aa4ccc2e953 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51d2cbb481908bc74cecdc023547 |
completed | March 8, 2026, 10:39 a.m. |
Created at: March 4, 2026, 7:28 p.m.