Triple
T16612071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cindy |
E403599
|
entity |
| Predicate | workRuntimeCharacteristic |
P52542
|
FINISHED |
| Object | short-lived series |
—
|
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: short-lived series | Statement: [Cindy, workRuntimeCharacteristic, short-lived series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workRuntimeCharacteristic Context triple: [Cindy, workRuntimeCharacteristic, short-lived series]
-
A.
runtimeCharacteristic
chosen
Indicates a relationship where a system, process, or component is associated with a property or behavior that specifically manifests during its execution or operation time.
-
B.
operationalCharacteristic
Indicates a relationship where a specific functional or performance trait is attributed to, or used to describe, how an entity operates.
-
C.
runtimeOfWork
Indicates the duration of time required to complete a particular work or task.
-
D.
workCharacter
Indicates that a person is a fictional or narrative character appearing in a particular creative work.
-
E.
trainingCharacteristic
Indicates that an entity has a specific property, feature, or quality related to training (such as method, intensity, or style).
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36096356c819092815d64db041793 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.