Triple
T27960210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiyuan era |
E704556
|
entity |
| Predicate | hasNotableChancellors |
P325
|
FINISHED |
| Object | Yao Chong |
—
|
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: Yao Chong | Statement: [Kaiyuan era, hasNotableChancellors, Yao Chong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableChancellors Context triple: [Kaiyuan era, hasNotableChancellors, Yao Chong]
-
A.
hasChancellor
chosen
Indicates that an entity holds the position or role of chancellor for another entity.
-
B.
hadFinanceMinister
Indicates that a country or governing body was served by a specific individual in the role of finance minister.
-
C.
hasNotableStatesman
Indicates that an entity is associated with or distinguished by a prominent political leader or statesman.
-
D.
hasNotablePolis
Indicates that an entity is associated with or contains a city-state (polis) that is considered notable or significant.
-
E.
notablePrimeMinisterHolder
Indicates that the subject has served as a particularly notable or distinguished prime minister of the object 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: April 27, 2026, 7:31 p.m.