Triple
T30164977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mursili I |
E766769
|
entity |
| Predicate | successorStateAffected |
P197022
|
FINISHED |
| Object | Old Babylonian Kingdom |
—
|
NE NERFINISHED |
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: Old Babylonian Kingdom | Statement: [Mursili I, successorStateAffected, Old Babylonian Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorStateAffected Context triple: [Mursili I, successorStateAffected, Old Babylonian Kingdom]
-
A.
successorState
Indicates that one state directly follows another as the immediate next state in a sequence or process.
-
B.
successorStateFlag
Indicates that a particular state directly follows another state in a defined sequence or process.
-
C.
successorStateUse
Indicates that one state or condition directly follows and is used as the next state resulting from a prior state or action.
-
D.
successorStateContributedTo
Indicates that a later state or condition was partially caused, influenced, or brought about by an earlier contributing state.
-
E.
successorStateRelations
Indicates the state transitions that directly follow from a given state, capturing how one state leads to its immediate successor states.
- 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_69f2247a968881909d79c18f2bfcb275 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
| PDg | Predicate description generation | batch_69fe744e9ee081909b362fc8609bc744 |
completed | May 8, 2026, 11:39 p.m. |
Created at: April 29, 2026, 7:23 p.m.