Triple

T38476536
Position Surface form Disambiguated ID Type / Status
Subject David Mason E915563 entity
Predicate notableMission P68 FINISHED
Object “Old Wounds” (framing narrative)
“Old Wounds” is a framing narrative in the Call of Duty: Black Ops II campaign that follows CIA agent David Mason as he investigates his father’s past missions and the origins of terrorist leader Raul Menendez.
E2271245 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: “Old Wounds” (framing narrative) | Statement: [David Mason, notableMission, “Old Wounds” (framing narrative)]
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: “Old Wounds” (framing narrative)
Triple: [David Mason, notableMission, “Old Wounds” (framing narrative)]
Generated description
“Old Wounds” is a framing narrative in the Call of Duty: Black Ops II campaign that follows CIA agent David Mason as he investigates his father’s past missions and the origins of terrorist leader Raul Menendez.

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_69f76e8ff5cc8190a88803369183845e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd21e1c8c819084ab99827ceaaf6c completed May 7, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ccbec9948190aa200f63d70381c3 completed June 29, 2026, 1:39 a.m.
NEDg Description generation batch_6a41ce5b4f0c8190bcfc3e29c6f0934f completed June 29, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_6a41cedbcb84819097e19d33da9ba767 completed June 29, 2026, 1:48 a.m.
Created at: May 3, 2026, 4:31 p.m.