Triple
T3308110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Bayyinah |
E69500
|
entity |
| Predicate | describesPunishmentAs |
P30305
|
FINISHED |
| Object | Hellfire |
—
|
LITERAL 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: Hellfire | Statement: [Surah Al-Bayyinah, describesPunishmentAs, Hellfire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesPunishmentAs Context triple: [Surah Al-Bayyinah, describesPunishmentAs, Hellfire]
-
A.
punishedBy
Indicates that an entity receives punishment administered by another entity.
-
B.
punishmentLocation
chosen
Indicates the place or setting where a punishment is carried out or imposed.
-
C.
hasPunishment
Indicates that an entity is subject to a specified penalty, sanction, or adverse consequence as a result of some action, condition, or rule.
-
D.
sentencedTo
Indicates that an authority has officially assigned a specific punishment or penalty to an entity, typically as the outcome of a legal or disciplinary process.
-
E.
violationConsequences
Indicates the negative outcomes, penalties, or repercussions that result from a violation of a rule, law, or agreement.
- F. None of above.
Provenance (3 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0cc15088190b51c311c6590df04 |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.