Triple
T27766537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sima Yan |
E701614
|
entity |
| Predicate | successorStateUnified |
P3025
|
FINISHED |
| Object | Jin 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: Jin dynasty | Statement: [Sima Yan, successorStateUnified, Jin dynasty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorStateUnified Context triple: [Sima Yan, successorStateUnified, Jin dynasty]
-
A.
successorState
chosen
Indicates that one state directly follows another as the immediate next state in a sequence or process.
-
B.
successorStateOver
Indicates that one state directly follows another in an ordered progression or sequence over a given dimension or context.
-
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.
successorStateFlag
Indicates that a particular state directly follows another state in a defined sequence or process.
-
E.
successorStateSite
Indicates that one site or state of a site directly follows another as its immediate successor in a sequence or process.
- 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_69ef6a52fa708190934a32308d2c92dc |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 27, 2026, 4:31 p.m.