Triple
T3098485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount of Beatitudes (traditional site) |
E64657
|
entity |
| Predicate | hasReligiousSymbol |
P5607
|
FINISHED |
| Object | crosses |
—
|
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: crosses | Statement: [Mount of Beatitudes (traditional site), hasReligiousSymbol, crosses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousSymbol Context triple: [Mount of Beatitudes (traditional site), hasReligiousSymbol, crosses]
-
A.
hasNoReligiousSymbol
Indicates that an entity does not display, contain, or is not associated with any religious symbol.
-
B.
hasSacredSymbol
chosen
Indicates that one entity serves as a sacred or religiously significant symbol associated with another entity.
-
C.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
D.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
E.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23dde988190a1aca020685594f3 |
completed | March 8, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.