Triple
T32368282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Ai of Tang |
E827057
|
entity |
| Predicate | titleBeforeReign |
P79021
|
FINISHED |
| Object | Prince of Wei |
—
|
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: Prince of Wei | Statement: [Emperor Ai of Tang, titleBeforeReign, Prince of Wei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleBeforeReign Context triple: [Emperor Ai of Tang, titleBeforeReign, Prince of Wei]
-
A.
titleBeforeEmperor
chosen
Indicates that one entity held a particular title or rank prior to becoming emperor.
-
B.
titleReign
Indicates the period during which a particular title was officially held or exercised by an entity.
-
C.
namedAfterReignTitle
Indicates that something is named after the official title held by a ruler during their reign.
-
D.
associatedTitleAfterEnthronement
Indicates the formal title or designation that is linked to an individual specifically after they have been enthroned or installed in an official position.
-
E.
titleHeldBeforeSuccession
Indicates that an entity held a specific title or position prior to a particular succession event.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: May 1, 2026, 12:50 a.m.