Triple

T35292134
Position Surface form Disambiguated ID Type / Status
Subject Denise Galik E1019255 entity
Predicate notableWork P4 FINISHED
Object The Incredible Melting Man
The Incredible Melting Man is a 1977 American science fiction horror film about an astronaut who begins to gruesomely melt after a space mission exposes him to deadly radiation.
E2134870 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: The Incredible Melting Man | Statement: [Denise Galik, notableWork, The Incredible Melting Man]
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: The Incredible Melting Man
Triple: [Denise Galik, notableWork, The Incredible Melting Man]
Generated description
The Incredible Melting Man is a 1977 American science fiction horror film about an astronaut who begins to gruesomely melt after a space mission exposes him to deadly radiation.

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_69f76de7eedc8190a3bdc64ebbc05b42 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f79014fb808190888700c2a4887905 completed May 3, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819e150648190877afa433023cebc completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381aa671a08190a3a1b66d1ef5a93d completed June 21, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_6a381b3c8ecc8190a22b608d4cb29b2a completed June 21, 2026, 5:11 p.m.
Created at: May 3, 2026, 4:03 p.m.