Triple
T19646767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Winslow Boy |
E471692
|
entity |
| Predicate | hasRecurringLine |
P10543
|
FINISHED |
| Object | "Let right be done." |
—
|
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: "Let right be done." | Statement: [The Winslow Boy, hasRecurringLine, "Let right be done."]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringLine Context triple: [The Winslow Boy, hasRecurringLine, "Let right be done."]
-
A.
hasRecurringElement
chosen
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
B.
hasRecurringSpecial
Indicates that an entity regularly offers or features a special deal, item, or promotion that recurs over time.
-
C.
hasRecurringRole
Indicates that an entity repeatedly appears or participates in a role within an ongoing or multiple related contexts over time.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64125dd9481908a891c71c975a964 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.