Triple
T13872589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Lei |
E333490
|
entity |
| Predicate | careerStartAs |
P112203
|
FINISHED |
| Object | child actor |
—
|
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: child actor | Statement: [Wu Lei, careerStartAs, child actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerStartAs Context triple: [Wu Lei, careerStartAs, child actor]
-
A.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
B.
startedCareerWith
Indicates that an entity began its professional career associated with, employed by, or active for another specified entity.
-
C.
writingCareerStartAs
Indicates the point, role, or context in which an entity began its professional writing career.
-
D.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
-
E.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
- F. None of above. chosen
Provenance (4 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:14 p.m.