Triple
T22020594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master Sergeant Farell |
E543833
|
entity |
| Predicate | onScreenYear |
P79694
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [Master Sergeant Farell, onScreenYear, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onScreenYear Context triple: [Master Sergeant Farell, onScreenYear, 2014]
-
A.
onScreenYears
Indicates the span of years during which an entity appeared or was active on screen.
-
B.
firstScreeningYear
Indicates the year in which an entity (such as a film or show) was first publicly screened or premiered.
-
C.
screenDebutYear
chosen
Indicates the year in which an entity first appeared on screen (such as in film, television, or other recorded visual media).
-
D.
onScreenStatus
Indicates that an entity’s current presence or visibility state is being specified relative to a screen or display.
-
E.
originallyScheduledYear
Indicates the year in which something was first planned or scheduled to occur, before any later changes or rescheduling.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c7b3308190ac056bef6f82722e |
completed | April 28, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:23 p.m.