Triple
T25209390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarlett Amber Perkins |
E631639
|
entity |
| Predicate | meetsAgain |
P158035
|
FINISHED |
| Object | Nobody Owens as a teenager |
—
|
NE NERFINISHED |
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: Nobody Owens as a teenager | Statement: [Scarlett Amber Perkins, meetsAgain, Nobody Owens as a teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsAgain Context triple: [Scarlett Amber Perkins, meetsAgain, Nobody Owens as a teenager]
-
A.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
B.
meetsTo
Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
-
C.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
D.
meetsRegarding
Indicates that one entity meets with another specifically to discuss or address a particular topic, issue, or subject.
-
E.
meetsBetween
Indicates that one entity meets or encounters another at some point between two specified reference points or times.
- 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_69e75a8d1aa48190a4320acd3654762c |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f44d849e7c81909945438f40e35362 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 21, 2026, 12:58 p.m.