Triple
T9491581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Paul, Op. 36 |
E228902
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Paulus |
E8385
|
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: Paulus | Statement: [St. Paul, Op. 36, alsoKnownAs, Paulus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paulus Context triple: [St. Paul, Op. 36, alsoKnownAs, Paulus]
-
A.
Paulus
Paulus was an influential Roman jurist whose legal writings significantly shaped later compilations of Roman law.
-
B.
Apostle Paul
chosen
Apostle Paul was an early Christian missionary and theologian whose letters form a significant portion of the New Testament and profoundly shaped Christian doctrine.
-
C.
Paul
Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
-
D.
Paul
Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
-
E.
Paul
Paul is a character in the crime drama film "Never Die Alone," which follows the violent, intertwined lives of drug dealers and those around them.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c89ec48190a2ad49394cab9c56 |
completed | April 1, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a0331e08190b42df462c50e1f44 |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:56 p.m.