Triple
T7325944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taoyuan Leopards |
E168874
|
entity |
| Predicate | professionalStatusStartYear |
P67641
|
FINISHED |
| Object | 2021 |
—
|
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: 2021 | Statement: [Taoyuan Leopards, professionalStatusStartYear, 2021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalStatusStartYear Context triple: [Taoyuan Leopards, professionalStatusStartYear, 2021]
-
A.
studCareerStartYear
Indicates the calendar year in which a student's academic or educational career formally began.
-
B.
startTimeOfProfessionalCareer
chosen
Indicates the point in time when an individual’s professional career formally begins.
-
C.
workYear
Indicates the specific year or span of years during which an entity (such as a person or organization) was engaged in work or employment.
-
D.
contractStartYear
Indicates the calendar year in which a contract between parties officially begins.
-
E.
earliestOccupationDate
Indicates the earliest known date on which an entity began a particular occupation or role.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a612c08190b7a3fefa811bbcec |
completed | March 27, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.