Triple
T7266936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lana Turner |
E160998
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Turner |
E45991
|
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: Turner | Statement: [Lana Turner, familyName, Turner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turner Context triple: [Lana Turner, familyName, Turner]
-
A.
Turner
chosen
Turner is a common English surname borne by numerous notable individuals across politics, arts, sports, and entertainment.
-
B.
Turner Layton
Turner Layton was an American songwriter, pianist, and singer best known for co-writing popular early 20th-century standards such as "After You've Gone" and "Way Down Yonder in New Orleans."
-
C.
Tunner
Tunner is a surname most notably associated with William H. Tunner, a prominent U.S. Air Force general known for organizing major airlift operations such as the Berlin Airlift.
-
D.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
E.
Melville Tucker
Melville Tucker is a film producer best known for his work on the 1980 comedy movie "Stir Crazy."
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eae7b2108190a6910f6655669db5 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3cb62288190bac8da63c24fe076 |
completed | March 28, 2026, 1:12 p.m. |
Created at: March 27, 2026, 2:58 p.m.