Triple
T27748169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganlu |
E702043
|
entity |
| Predicate | hasEraSequencePosition |
P137790
|
FINISHED |
| Object | late era of Cao Wei |
—
|
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: late era of Cao Wei | Statement: [Ganlu, hasEraSequencePosition, late era of Cao Wei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEraSequencePosition Context triple: [Ganlu, hasEraSequencePosition, late era of Cao Wei]
-
A.
positionInEra
Indicates the temporal placement or role of something within a specific historical or chronological era.
-
B.
hasSequencePosition
chosen
Indicates that an element occupies a specific position or order within a sequence.
-
C.
hasEraReset
Indicates that a new era or time period has been initiated, resetting the previous temporal sequence or counting.
-
D.
hasPrimaryEra
Indicates that an entity is chiefly associated with or belongs to a particular historical or temporal era.
-
E.
representsEra
Indicates that one entity designates the historical era, period, or age to which another entity belongs or is associated.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 4:18 p.m.