Triple

T4622987
Position Surface form Disambiguated ID Type / Status
Subject Men in Black E101029 entity
Predicate character P662 FINISHED
Object Zed
Zed is the stern, no-nonsense head of the secret government agency overseeing extraterrestrial activity in the "Men in Black" film series.
 E456962 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: Zed | Statement: [Men in Black, character, Zed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zed
Context triple: [Men in Black, character, Zed]
  • A. Zan
    Zan is a collective term for a group of closely related Kartvelian languages spoken primarily in western Georgia, including Mingrelian and Laz.
  • B. Zev
    Zev is a masculine given name of Hebrew origin, commonly interpreted to mean "wolf."
  • C. Zeke
    Zeke is the Allied reporting name for the Mitsubishi A6M Zero, the famous Japanese carrier-based fighter aircraft used extensively during World War II.
  • D. Zeke
    Zeke is a central male character in the romantic comedy film "Think Like a Man," known for navigating modern dating dynamics alongside a group of friends influenced by a relationship advice book.
  • E. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • 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: Zed
Triple: [Men in Black, character, Zed]
Generated description
Zed is the stern, no-nonsense head of the secret government agency overseeing extraterrestrial activity in the "Men in Black" film series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zed
Target entity description: Zed is the stern, no-nonsense head of the secret government agency overseeing extraterrestrial activity in the "Men in Black" film series.
  • A. Zan
    Zan is a collective term for a group of closely related Kartvelian languages spoken primarily in western Georgia, including Mingrelian and Laz.
  • B. Zev
    Zev is a masculine given name of Hebrew origin, commonly interpreted to mean "wolf."
  • C. Zeke
    Zeke is a central male character in the romantic comedy film "Think Like a Man," known for navigating modern dating dynamics alongside a group of friends influenced by a relationship advice book.
  • D. Zeke
    Zeke is the Allied reporting name for the Mitsubishi A6M Zero, the famous Japanese carrier-based fighter aircraft used extensively during World War II.
  • E. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a053d38819097b3ecbc06aa6e4d completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaa069388190b6482315708b85c2 completed March 21, 2026, 1:55 a.m.
NEDg Description generation batch_69bdfb9422e48190819d5d99e72e8854 completed March 21, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc6ac91c819090776365d3dc05d4 completed March 21, 2026, 2:03 a.m.
Created at: March 20, 2026, 1:12 p.m.