Triple
T7955668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoshanna Shapiro |
E184728
|
entity |
| Predicate | romanticHistory |
P10693
|
FINISHED |
| Object | dates Ray Ploshansky and other men during the 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: dates Ray Ploshansky and other men during the series | Statement: [Shoshanna Shapiro, romanticHistory, dates Ray Ploshansky and other men during the series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticHistory Context triple: [Shoshanna Shapiro, romanticHistory, dates Ray Ploshansky and other men during the series]
-
A.
historicallyAttracted
Indicates that one entity has experienced attraction toward another at some point in the past.
-
B.
romanticArc
chosen
Indicates a developing or ongoing romantic relationship or storyline between the involved entities.
-
C.
historicalGenre
Indicates that something belongs to or is categorized within a particular historical genre.
-
D.
romanticReputation
Indicates how an entity is perceived or regarded by others in the context of romantic behavior, history, or involvement.
-
E.
historicalInterest
Indicates that one entity has a notable relevance, appeal, or significance to the study or understanding of the past.
- 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_69ca8292cba881908a64427b938dac47 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b60e9508190ad9974ad551bcbc6 |
completed | March 31, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69cb0473d7dc8190a25d0cf460b9fcbe |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:11 p.m.