Triple
T82800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soldier Field |
E1663
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object |
Wood + Zapata
Wood + Zapata is an architecture firm known for its role in the modern renovation and design work of major sports and public venues in the United States.
|
E5739
|
NE FINISHED |
How this triple was built (4 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 + Zapata | Statement: [Soldier Field, architect, Wood + Zapata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wood + Zapata Context triple: [Soldier Field, architect, Wood + Zapata]
-
A.
Milwaukee Deep
Milwaukee Deep is the deepest known point in the Atlantic Ocean, located within the Puerto Rico Trench.
-
B.
Stumptown
Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
-
C.
City of Trees
City of Trees is a popular nickname for Sacramento, California, highlighting its extensive urban tree canopy and lush greenery.
-
D.
Fall Weiss
Fall Weiss was the codename for Nazi Germany’s military plan to invade Poland in September 1939, marking the beginning of World War II in Europe.
-
E.
Dream Machines
Dream Machines is the visionary second half of Ted Nelson’s influential 1974 book that imagines interactive, hypertext-based computers as tools for personal creativity and liberation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wood + Zapata Triple: [Soldier Field, architect, Wood + Zapata]
Generated description
Wood + Zapata is an architecture firm known for its role in the modern renovation and design work of major sports and public venues in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wood + Zapata Target entity description: Wood + Zapata is an architecture firm known for its role in the modern renovation and design work of major sports and public venues in the United States.
-
A.
Milwaukee Deep
Milwaukee Deep is the deepest known point in the Atlantic Ocean, located within the Puerto Rico Trench.
-
B.
Stumptown
Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
-
C.
City of Trees
City of Trees is a popular nickname for Sacramento, California, highlighting its extensive urban tree canopy and lush greenery.
-
D.
Encore
Encore is a luxury casino and resort brand operated by Wynn Resorts, known for its upscale accommodations, gaming, dining, and entertainment offerings.
-
E.
Fall Weiss
Fall Weiss was the codename for Nazi Germany’s military plan to invade Poland in September 1939, marking the beginning of World War II in Europe.
- F. None of above. chosen
Provenance (5 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4ccb5081908decac81f4af01bf |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2555394f881909f01ec05c75ff63d |
completed | Feb. 28, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_69a256c4dc84819098c62b776c9ec80d |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a25781a51c8190b9a2ecbd2ef4ecae |
completed | Feb. 28, 2026, 2:48 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.