Triple

T34027339
Position Surface form Disambiguated ID Type / Status
Subject The Return of the Living Dead E872544 entity
Predicate featuresCharacter P626 FINISHED
Object Tarman
Tarman is an iconic, grotesquely decayed zombie known for his slimy appearance and craving for brains in the horror-comedy film "The Return of the Living Dead."
E2079057 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: Tarman | Statement: [The Return of the Living Dead, featuresCharacter, Tarman]
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: Tarman
Triple: [The Return of the Living Dead, featuresCharacter, Tarman]
Generated description
Tarman is an iconic, grotesquely decayed zombie known for his slimy appearance and craving for brains in the horror-comedy film "The Return of the Living Dead."

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_69f349a2527c81909a7cd4bda94d70ad completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70b1a993481908f80469dbaf1e1d8 completed May 3, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a02de97c8190bd15c74d8902cb80 completed June 20, 2026, 2:14 p.m.
NEDg Description generation batch_6a36a0de350081909525a0c212057a65 completed June 20, 2026, 2:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36a185fad881909585edc7f5d5c177 completed June 20, 2026, 2:19 p.m.
Created at: May 1, 2026, 1:51 a.m.