Triple
T5354659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysias |
E102660
|
entity |
| Predicate | roleDuringMaccabeanRevolt |
P63205
|
FINISHED |
| Object | leader of royal Seleucid forces |
—
|
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: leader of royal Seleucid forces | Statement: [Lysias, roleDuringMaccabeanRevolt, leader of royal Seleucid forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringMaccabeanRevolt Context triple: [Lysias, roleDuringMaccabeanRevolt, leader of royal Seleucid forces]
-
A.
roleDuringCrusades
Indicates the specific function, position, or involvement an entity had in relation to the Crusades during the period they occurred.
-
B.
roleInAmericanRevolution
Indicates that an entity had a specific role, position, or involvement in events or activities related to the American Revolution.
-
C.
roleInIsrael
Indicates that an entity holds or held a specific role, position, or function within the context of Israel.
-
D.
roleInMutiny
Indicates that one entity participated in a mutiny with a specific role or capacity in that rebellious action.
-
E.
roleInJudaism
Indicates the specific religious, social, or institutional function an entity holds within the context of Judaism.
- 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_69bd43d8f7248190b64c140734b5c9a8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd862dbb008190aef653acddafd38b |
completed | March 20, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69bd845c6f108190832a8d14b356368a |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd85e69e808190b29548670fd2900a |
completed | March 20, 2026, 5:37 p.m. |
Created at: March 20, 2026, 2:01 p.m.