Triple
T14691363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army of the Dead |
E345041
|
entity |
| Predicate | leadCharacter |
P1668
|
FINISHED |
| Object |
Scott Ward
Scott Ward is the battle-hardened former soldier who leads a team of mercenaries into zombie-infested Las Vegas in Zack Snyder’s film "Army of the Dead."
|
E1116635
|
NE FINISHED |
How this triple was built (4 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: Scott Ward | Statement: [Army of the Dead, leadCharacter, Scott Ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Ward Context triple: [Army of the Dead, leadCharacter, Scott Ward]
-
A.
Graham Wardle
Graham Wardle is a Canadian actor best known for playing Ty Borden on the long-running family drama television series "Heartland."
-
B.
Michael Wright
Michael Wright is an American actor known for his roles in films and television series such as "The Five Heartbeats," "Sugar Hill," and the HBO series "Oz."
-
C.
Douglas Warrick
Douglas Warrick is a biologist known for his research on animal flight biomechanics, particularly in birds.
-
D.
Mark Wright
Mark Wright is an American country music producer and record executive known for his work with numerous prominent artists and hit albums.
-
E.
Chris Ward
Chris Ward is a relatively common personal name shared by multiple individuals across fields such as sports, politics, and the arts.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Scott Ward Triple: [Army of the Dead, leadCharacter, Scott Ward]
Generated description
Scott Ward is the battle-hardened former soldier who leads a team of mercenaries into zombie-infested Las Vegas in Zack Snyder’s film "Army of the Dead."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scott Ward Target entity description: Scott Ward is the battle-hardened former soldier who leads a team of mercenaries into zombie-infested Las Vegas in Zack Snyder’s film "Army of the Dead."
-
A.
Graham Wardle
Graham Wardle is a Canadian actor best known for playing Ty Borden on the long-running family drama television series "Heartland."
-
B.
Michael Wright
Michael Wright is an American actor known for his roles in films and television series such as "The Five Heartbeats," "Sugar Hill," and the HBO series "Oz."
-
C.
Douglas Warrick
Douglas Warrick is a biologist known for his research on animal flight biomechanics, particularly in birds.
-
D.
Mark Wright
Mark Wright is an American country music producer and record executive known for his work with numerous prominent artists and hit albums.
-
E.
Chris Ward
Chris Ward is a relatively common personal name shared by multiple individuals across fields such as sports, politics, and the arts.
- F. None of above. chosen
Provenance (5 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb585d46c81908d6964130914cec4 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb807af081908dd56caf3d06550f |
completed | May 8, 2026, 3:04 p.m. |
| NEDg | Description generation | batch_69fdfdfabca88190ab7b173febf7bea1 |
completed | May 8, 2026, 3:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdfe624dd88190986cca4b1d71d002 |
completed | May 8, 2026, 3:16 p.m. |
Created at: April 10, 2026, 1:28 a.m.