Triple

T31675001
Position Surface form Disambiguated ID Type / Status
Subject Surah Fatir E808374 entity
Predicate containsVerseAbout P28117 FINISHED
Object the parable of darkness and light
The parable of darkness and light is a Qur’anic metaphor in Surah Fatir contrasting disbelief and faith through the imagery of obscurity versus illumination.
E1260824 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 parable of darkness and light | Statement: [Surah Fatir, containsVerseAbout, the parable of darkness and light]
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 parable of darkness and light
Triple: [Surah Fatir, containsVerseAbout, the parable of darkness and light]
Generated description
The parable of darkness and light is a Qur’anic metaphor in Surah Fatir contrasting disbelief and faith through the imagery of obscurity versus illumination.

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_69f348dcf5d48190ac25b1365ae717a8 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa51a5e081909f733cb0bbf4e1c5 completed May 3, 2026, 1:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84b4eb5481909fb606611b607aff completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b857dd8708190984e04b26d63e120 completed June 12, 2026, 4:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8682a4a8819097f791a41a5c6274 completed June 12, 2026, 4:09 a.m.
Created at: April 30, 2026, 11:02 p.m.