Triple
T7815237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Berko Gleason |
E180987
|
entity |
| Predicate | hasTestNamedAfterHer |
P79163
|
FINISHED |
| Object | wug test |
E694780
|
NE FINISHED |
How this triple was built (3 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: wug test | Statement: [Jean Berko Gleason, hasTestNamedAfterHer, wug test]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: wug test Context triple: [Jean Berko Gleason, hasTestNamedAfterHer, wug test]
-
A.
wug test
chosen
The wug test is a classic psycholinguistic experiment that demonstrates children’s ability to apply grammatical rules to novel, made-up words.
-
B.
WUG
WUG is the vehicle registration code for the Weißenburg-Gunzenhausen district in Middle Franconia, Bavaria, Germany.
-
C.
WU
WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
-
D.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
-
E.
WÜ
WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTestNamedAfterHer Context triple: [Jean Berko Gleason, hasTestNamedAfterHer, wug test]
-
A.
lastTestFor
Indicates that one entity is the most recent test or examination performed for another entity.
-
B.
hasWorkNamedAfter
Indicates that one entity has a work (such as a book, artwork, or composition) that is named after or titled with reference to another entity.
-
C.
testName
Indicates that an entity is identified or labeled by a specific test name.
-
D.
hasCollectionNamedAfter
Indicates that an entity has a collection (e.g., of works, items, or artifacts) that is named in honor of or after another entity.
-
E.
hasSymbolNamedAfter
Indicates that one entity has a symbol whose name is derived from or dedicated to another entity.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96d1f088190a1d005ffb019afe9 |
completed | March 30, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a5c24908190847b612a56a1abf5 |
completed | March 31, 2026, 5:23 a.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:39 p.m.