Triple
T12238642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne McAllister |
E291667
|
entity |
| Predicate | style |
P87
|
FINISHED |
| Object | Googie |
E175628
|
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: Googie | Statement: [Wayne McAllister, style, Googie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Googie Context triple: [Wayne McAllister, style, Googie]
-
A.
Googie
chosen
Googie is a futuristic, space-age style of mid-20th-century American architecture characterized by bold angles, upswept roofs, and neon-lit signage, often associated with coffee shops, motels, and roadside attractions.
-
B.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
-
C.
Goopy
Goopy is the bumbling, music-loving protagonist of Satyajit Ray’s classic Bengali fantasy film "Goopy Gyne Bagha Byne."
-
D.
Goode
Goode is an English surname borne by various notable individuals across fields such as acting, politics, and academia.
-
E.
GOO
GOO is the National Rail station code for Goole railway station in the East Riding of Yorkshire, England.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb45340819093365f8efdf85f75 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60ab3ae2481908f65d8ac61a6b2e4 |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:51 p.m.