Triple
T33857238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gongnie |
E867817
|
entity |
| Predicate | successorStatePeriod |
P200885
|
FINISHED |
| Object | Eastern Zhou period began after his death |
—
|
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: Eastern Zhou period began after his death | Statement: [Gongnie, successorStatePeriod, Eastern Zhou period began after his death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorStatePeriod Context triple: [Gongnie, successorStatePeriod, Eastern Zhou period began after his death]
-
A.
successorState
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.
successorStateFlag
Indicates that a particular state directly follows another state in a defined sequence or process.
-
D.
historicalSuccessorState
Indicates that one state historically followed and replaced another state in time as its successor.
-
E.
successorStateRepresentedLater
Indicates that one state is a later representation or subsequent version of another state in a temporal or sequential progression.
- 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_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffb69812808190a751853b30183e65 |
completed | May 9, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69ffb63bdda88190a9dd8426dc0bad43 |
completed | May 9, 2026, 10:33 p.m. |
| PDg | Predicate description generation | batch_69ffb6976f84819098a9b14946591baa |
completed | May 9, 2026, 10:35 p.m. |
Created at: May 1, 2026, 1:47 a.m.