Triple
T14429168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John F. Seitz |
E357775
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Blood and Sand |
E13180
|
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: Blood and Sand | Statement: [John F. Seitz, notableWork, Blood and Sand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blood and Sand Context triple: [John F. Seitz, notableWork, Blood and Sand]
-
A.
Blood and Sand
chosen
Blood and Sand is a 1922 silent drama film starring Rudolph Valentino as a rising bullfighter whose fame leads to personal and moral downfall.
-
B.
Blood and Sand
Blood and Sand is a 1941 Technicolor drama film starring Tyrone Power and Rita Hayworth, renowned for its lavish production and tragic tale of a Spanish bullfighter.
-
C.
Blood and Sand
Blood and Sand is a notable work by Edward Snyder, best known as a dramatic play exploring themes of passion, betrayal, and moral conflict.
-
D.
La malasangre
La malasangre is a notable dramatic work associated with Argentine actress and director Cristina Banegas.
-
E.
Black Mischief
Black Mischief is a satirical novel by Evelyn Waugh that lampoons British imperialism and modernizing schemes in a fictional African kingdom.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91154de881909266ae88d1545685 |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bd1c4d0819085edb9ed22128b68 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:18 a.m.