Triple
T5012416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwen May-Wan Kao |
E112655
|
entity |
| Predicate | supportedWorkIn |
P27740
|
FINISHED |
| Object | fiber-optic communications |
—
|
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: fiber-optic communications | Statement: [Gwen May-Wan Kao, supportedWorkIn, fiber-optic communications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportedWorkIn Context triple: [Gwen May-Wan Kao, supportedWorkIn, fiber-optic communications]
-
A.
supportedByWork
Indicates that one entity’s existence, validity, or outcome is backed, justified, or enabled by the work or efforts of another entity.
-
B.
supportedWork
Indicates that one entity provides assistance, resources, or endorsement to enable or sustain the work or activity of another entity.
-
C.
worksTo
chosen
Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
-
D.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
E.
eligibleWorks
Indicates that certain works meet the required criteria or conditions to qualify for a specified status, use, or consideration.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730f12a481908a27c15dc73987c6 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.