Triple
T15472425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Bibb |
E376694
|
entity |
| Predicate | hasBeenActiveIn |
P19746
|
FINISHED |
| Object | film |
—
|
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: film | Statement: [Leslie Bibb, hasBeenActiveIn, film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenActiveIn Context triple: [Leslie Bibb, hasBeenActiveIn, film]
-
A.
hasRecentActivity
Indicates that the subject has performed an action or been involved in an event within a defined recent time period.
-
B.
hasActivityIn
chosen
Indicates that an entity engages in or performs a particular activity within a specified context, location, or domain.
-
C.
hasEvidenceOfActivitySince
Indicates that there is evidence showing an entity has been active or engaged in some activity from a specified point in time onward.
-
D.
activeAt
Indicates that an entity is functioning, valid, or in effect during a specified time or at a particular location or context.
-
E.
hasOnlineActivity
Indicates that an entity engages in or possesses some form of activity or presence on the internet or digital platforms.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6c57308190b4cfe661c26addd4 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:33 a.m.