Triple

T25199478
Position Surface form Disambiguated ID Type / Status
Subject Metal Gear Solid E631086 entity
Predicate character P662 FINISHED
Object Naomi Hunter
Naomi Hunter is a geneticist and FOXHOUND medical specialist in the Metal Gear Solid series, known for her complex ties to Solid Snake and pivotal role in the story’s biotechnological conspiracies.
E1677862 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: Naomi Hunter | Statement: [Metal Gear Solid, character, Naomi Hunter]
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: Naomi Hunter
Triple: [Metal Gear Solid, character, Naomi Hunter]
Generated description
Naomi Hunter is a geneticist and FOXHOUND medical specialist in the Metal Gear Solid series, known for her complex ties to Solid Snake and pivotal role in the story’s biotechnological conspiracies.

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_69e75a8b86c4819089eda22c843b739f completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f474b512348190b33fc57f03490515 completed May 1, 2026, 9:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1075c76bb48190b88f52f758d8f1ac completed May 22, 2026, 3:27 p.m.
NEDg Description generation batch_6a1079d95d1c819093e5780a2f3c1532 completed May 22, 2026, 3:44 p.m.
NED2 Entity disambiguation (via description) batch_6a107a9277848190b817ac608347ad3e completed May 22, 2026, 3:47 p.m.
Created at: April 21, 2026, 12:51 p.m.