Triple
T14299984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gustav Stickley |
E354536
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gustav |
E140654
|
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: Gustav | Statement: [Gustav Stickley, givenName, Gustav]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gustav Context triple: [Gustav Stickley, givenName, Gustav]
-
A.
Gustav
chosen
Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
-
B.
Gustaf
Gustaf is the given name of Carl Gustaf Emil Mannerheim, the Finnish military leader and statesman who served as Commander-in-Chief during World War II and later as President of Finland.
-
C.
Wilhelm
Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
-
D.
Ludwig
Ludwig is a masculine given name of Germanic origin, historically associated with nobility and rulers and used in various forms across many European languages.
-
E.
Ludwig
Ludwig is a 1973 historical drama film by Italian director Luchino Visconti that portrays the life and tragic decline of Bavaria’s King Ludwig II.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717e246c819083e67ac2b3b77881 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4682f86881908c9fb210bb9e486a |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:11 a.m.