Triple

T26683012
Position Surface form Disambiguated ID Type / Status
Subject Dardo E672665 entity
Predicate appearsIn P795 FINISHED
Object 1950 film The Flame and the Arrow
The 1950 film "The Flame and the Arrow" is a swashbuckling adventure movie starring Burt Lancaster as a Robin Hood–like archer leading a rebellion in medieval Lombardy.
E1738651 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: 1950 film The Flame and the Arrow | Statement: [Dardo, appearsIn, 1950 film The Flame and the Arrow]
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: 1950 film The Flame and the Arrow
Triple: [Dardo, appearsIn, 1950 film The Flame and the Arrow]
Generated description
The 1950 film "The Flame and the Arrow" is a swashbuckling adventure movie starring Burt Lancaster as a Robin Hood–like archer leading a rebellion in medieval Lombardy.

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_69eecda13424819092b17942c4edf722 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6173afcd881908356903457eef60e completed May 2, 2026, 3:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe78262481909322a3c31687b486 completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff4907e88190aaad22b7390bc094 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a120048ef6c8190bf4467e0742a0421 completed May 23, 2026, 7:30 p.m.
Created at: April 27, 2026, 3:21 a.m.