Triple
T9138936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Mexican Empire |
E219272
|
entity |
| Predicate | hasSuccessorStateForm |
P52817
|
FINISHED |
| Object | republic |
—
|
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: republic | Statement: [Second Mexican Empire, hasSuccessorStateForm, republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuccessorStateForm Context triple: [Second Mexican Empire, hasSuccessorStateForm, republic]
-
A.
successorStateForm
chosen
Indicates that one state or condition is the resulting or next state that directly follows another in a defined process or sequence.
-
B.
successorState
Indicates that one state directly follows another as the immediate next state in a sequence or process.
-
C.
appliesToSuccessorState
Indicates that the relationship or condition holds not in the current state but in the immediately following (successor) state of the system or process.
-
D.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
-
E.
hasFAASuccessorCode
Indicates that one entity is the FAA-assigned successor code that replaces or follows another entity’s previous FAA code.
- F. None of above.
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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8f129c08190b6f053984cb7363f |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.