Triple
T31399749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kafir (religious term) |
E800963
|
entity |
| Predicate | isConsideredSensitiveTermIn |
P177583
|
FINISHED |
| Object | interfaith dialogue |
—
|
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: interfaith dialogue | Statement: [Kafir (religious term), isConsideredSensitiveTermIn, interfaith dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isConsideredSensitiveTermIn Context triple: [Kafir (religious term), isConsideredSensitiveTermIn, interfaith dialogue]
-
A.
containsProfanity
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
-
B.
coCensorWith
Indicates that two or more entities participate together in the act of censoring the same content or subject.
-
C.
politicallySensitive
Indicates that an entity, action, or topic is associated with political issues, controversies, or power structures such that it may require special caution, regulation, or discretion.
-
D.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
-
E.
featuresProfanity
Indicates that the referenced content contains profane, vulgar, or offensive language.
- F. None of above. chosen
Provenance (4 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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: April 29, 2026, 9:19 p.m.