Triple
T13902652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve (Him & Her) |
E334263
|
entity |
| Predicate | onScreenYears |
P111948
|
FINISHED |
| Object | 2010–2013 |
—
|
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: 2010–2013 | Statement: [Steve (Him & Her), onScreenYears, 2010–2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onScreenYears Context triple: [Steve (Him & Her), onScreenYears, 2010–2013]
-
A.
productionYears
Indicates the span of calendar years during which something was produced or manufactured.
-
B.
coversYearsTo
Indicates a temporal relationship where one entity spans, includes, or extends up to a specified year or range of years represented by the other entity.
-
C.
firstScreeningYear
Indicates the year in which an entity (such as a film or show) was first publicly screened or premiered.
-
D.
screenDebutYear
Indicates the year in which an entity first appeared on screen (such as in film, television, or other recorded visual media).
-
E.
yearListed
Indicates the specific year in which an entity was formally recorded, registered, or added to a list or catalog.
- F. None of above. chosen
Provenance (4 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d9c7a48190ad8fb0ca676f4f7b |
completed | April 14, 2026, 11:32 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:16 p.m.