Triple
T35779219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Who Pacifies the West |
E1034388
|
entity |
| Predicate | holderLaterAllegiantTo |
P102641
|
FINISHED |
| Object | Qing 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: Qing dynasty | Statement: [Prince Who Pacifies the West, holderLaterAllegiantTo, Qing dynasty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holderLaterAllegiantTo Context triple: [Prince Who Pacifies the West, holderLaterAllegiantTo, Qing dynasty]
-
A.
hadAllegiance
Indicates that an entity was loyally committed or formally bound in support or service to another entity, such as a person, group, or cause.
-
B.
namedForAllegiance
Indicates that an entity is named in reference to, or in honor of, a particular allegiance, affiliation, or loyalty.
-
C.
stateAllegiance
Indicates that one entity formally declares loyalty or support to another entity, such as a person, group, or state.
-
D.
hasAuthorAllegiance
Indicates that an author is affiliated with, loyal to, or aligned with a particular group, organization, cause, or ideology.
-
E.
allegianceArc
chosen
Indicates a change or evolution in an entity’s loyalty or allegiance to another entity over time.
- 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_69f76e14a1e081908eddd57bd6fdb3be |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.