Triple
T24322906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lê Trang Tông |
E613016
|
entity |
| Predicate | successorStateOpponent |
P155553
|
FINISHED |
| Object | Mạc dynasty |
—
|
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: Mạc dynasty | Statement: [Lê Trang Tông, successorStateOpponent, Mạc dynasty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorStateOpponent Context triple: [Lê Trang Tông, successorStateOpponent, Mạc dynasty]
-
A.
successorState
Indicates that one state directly follows another as the immediate next state in a sequence or process.
-
B.
opponentState
Indicates the condition or status that an opposing party or competitor is currently in within a given context or interaction.
-
C.
successorStateSide2
Indicates that one state directly follows another as its immediate successor in the second dimension, perspective, or side of a state-transition relation.
-
D.
successorStateFlag
Indicates that a particular state directly follows another state in a defined sequence or process.
-
E.
successorStateLoss
Indicates that one state or condition directly follows another as a result of a loss event or losing transition.
- 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_69e2d7db6d5c819091194918157a7c1f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292ad4cc881908794b501cf70b7a1 |
completed | April 29, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f1c45f45888190a9ccc225906c34bd |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 1:52 a.m.