Triple
T49405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curse of the Bambino |
E971
|
entity |
| Predicate | allegedEffect |
P812
|
FINISHED |
| Object | Boston Red Sox World Series championship drought |
—
|
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: Boston Red Sox World Series championship drought | Statement: [Curse of the Bambino, allegedEffect, Boston Red Sox World Series championship drought]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedEffect Context triple: [Curse of the Bambino, allegedEffect, Boston Red Sox World Series championship drought]
-
A.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
B.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
C.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c1a5c14819088748317a3f262c8 |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24abfa7bc8190932c137a823efcb6 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.