Triple
T34113549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Zhu |
E874903
|
entity |
| Predicate | succeededOnThroneAsMinor |
P16541
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Li Zhu, succeededOnThroneAsMinor, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: succeededOnThroneAsMinor Context triple: [Li Zhu, succeededOnThroneAsMinor, true]
-
A.
cameToPowerAsMinor
chosen
Indicates that an individual assumed ruling authority or leadership while still legally or socially considered a minor.
-
B.
succeededOnThroneAs
Indicates that one entity became the next ruler on a throne directly after another entity, taking over their position of sovereignty.
-
C.
succeededToThroneBy
Indicates that one ruler or monarch is followed in succession by another who takes over the throne.
-
D.
succeededOnThroneAfter
Indicates that one entity became the ruler or monarch immediately following another entity’s reign on the same throne.
-
E.
succeededToThrone
Indicates that one entity became the new ruler by taking over the throne previously held by another entity.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: May 1, 2026, 1:53 a.m.