Triple
T1691495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Alston |
E36558
|
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 Alston, givenName, Walter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walter Context triple: [Walter Alston, givenName, Walter]
-
A.
Walter
chosen
Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
B.
Wilbert
Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
-
C.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
D.
Sterling Relyea Walter
Sterling Relyea Walter was the birth name of American actor and author Sterling Hayden, known for his roles in classic films such as "The Asphalt Jungle" and "Dr. Strangelove."
-
E.
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.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6298fa748190acabb9f1d42bd3f5 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada976b6cc8190b1f50452a73e142a |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:29 p.m.