Triple
T5048893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humana Building |
E113735
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object | Michael Graves |
E130211
|
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: Michael Graves | Statement: [Humana Building, architect, Michael Graves]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Graves Context triple: [Humana Building, architect, Michael Graves]
-
A.
Michael Graves
chosen
Michael Graves was an influential American architect and designer renowned for his colorful, playful postmodern buildings and widely popular product designs.
-
B.
Laurie Olin
Laurie Olin is a prominent American landscape architect and urban designer known for shaping major public spaces in cities across the United States.
-
C.
John Pawson
John Pawson is a British architect renowned for his minimalist designs and refined use of light, space, and materials.
-
D.
Thom Mayne
Thom Mayne is an American architect and founder of the firm Morphosis, known for his bold, unconventional designs and influential role in contemporary architecture.
-
E.
Peter Chermayeff
Peter Chermayeff is an American architect renowned for designing major public aquariums around the world.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7401419081909ba62b9c27f770c4 |
completed | March 20, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0f746788190bf73b8b5069e89cb |
completed | March 21, 2026, 2:53 p.m. |
Created at: March 20, 2026, 1:37 p.m.