Triple
T779765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Model |
E16469
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Walter |
E32053
|
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: Walter | Statement: [Walter Model, givenName, Walter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walter Context triple: [Walter Model, givenName, Walter]
-
A.
Walter
chosen
Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
B.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
C.
Ralph Stackpole
Ralph Stackpole was an American sculptor and painter associated with the San Francisco art scene, known for his public works and contributions to New Deal–era projects.
-
D.
Harold
Harold is a masculine given name of Old English origin, historically borne by several notable figures including kings and modern public personalities.
-
E.
Gerald
Gerald is the birth name of Jerry Brown, the longtime Democratic politician and former governor of California.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a750c6708190a3f2c3abf16b4ea4 |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c70e6eb48190b019759cd656e629 |
completed | March 4, 2026, 5:45 a.m. |
Created at: March 1, 2026, 7:37 p.m.