Triple
T15186181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genesis Rodriguez |
E362880
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Last Stand |
E550148
|
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: The Last Stand | Statement: [Genesis Rodriguez, notableWork, The Last Stand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Last Stand Context triple: [Genesis Rodriguez, notableWork, The Last Stand]
-
A.
The Last Stand
chosen
The Last Stand is a 2013 American action film starring Arnold Schwarzenegger as a small-town sheriff facing off against an escaped drug lord.
-
B.
The Last Stand
The Last Stand is a work by author David Harris, likely a book that reflects his focus on historical and political subjects.
-
C.
The Last Shot
The Last Shot is a 2004 crime-comedy film that satirizes Hollywood and the FBI by following a fake movie production used as a sting operation against the mob.
-
D.
Standoff
Standoff is a television series featuring Ron Livingston in a leading role as an FBI crisis negotiator.
-
E.
The Standoff
The Standoff is a crime thriller novel by Chuck Hogan that helped establish his reputation for tense, character-driven suspense fiction.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec895b59c81908a09f8393a35aa13 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:09 a.m.