Triple
T37146511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Barcelona (801) |
E920254
|
entity |
| Predicate | hasReligionOfAttackers |
P26483
|
FINISHED |
| Object | Christianity |
E348
|
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: Christianity | Statement: [Siege of Barcelona (801), hasReligionOfAttackers, Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionOfAttackers Context triple: [Siege of Barcelona (801), hasReligionOfAttackers, Christianity]
-
A.
religionOfPerpetrators
chosen
Indicates the religious affiliation or belief system associated with the individuals who carried out a particular act or offense.
-
B.
hasReligionOfBelligerents
Indicates that the belligerent parties in a conflict are associated with a particular religion or religious affiliation.
-
C.
religionOfDefenders
Indicates the religious affiliation practiced or associated with the defenders in a given context.
-
D.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
E.
hasDefendantReligion
Indicates that a specified religion is the religious affiliation of the defendant in a legal case.
- F. None of above.
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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3f6a2773ac8190928c55ab86886f55 |
completed | June 27, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.