Triple
T27805498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuḥfat al-Mawdūd bi Aḥkām al-Mawlūd |
E702364
|
entity |
| Predicate | religiousField |
P56366
|
FINISHED |
| Object | Islamic law (fiqh) |
—
|
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: Islamic law (fiqh) | Statement: [Tuḥfat al-Mawdūd bi Aḥkām al-Mawlūd, religiousField, Islamic law (fiqh)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousField Context triple: [Tuḥfat al-Mawdūd bi Aḥkām al-Mawlūd, religiousField, Islamic law (fiqh)]
-
A.
religiousEnvironment
Indicates the religious context, atmosphere, or setting in which an entity exists or an action takes place.
-
B.
religiousFoundation
Indicates that an entity was established, created, or founded by a religious organization, authority, or tradition.
-
C.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
D.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
E.
religionOrBelief
chosen
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
- 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_69ef8408e0588190977cffa32dc33a29 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 27, 2026, 5:38 p.m.