Triple
T1327851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1972 MLB strike |
E28370
|
entity |
| Predicate | firstIn |
P22901
|
FINISHED |
| Object | first players' strike in Major League Baseball history |
—
|
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: first players' strike in Major League Baseball history | Statement: [1972 MLB strike, firstIn, first players' strike in Major League Baseball history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstIn Context triple: [1972 MLB strike, firstIn, first players' strike in Major League Baseball history]
-
A.
firstWord
Indicates that one entity is the first word in the sequence or text associated with another entity.
-
B.
firstOf
Indicates that one entity is the earliest or initial member in an ordered sequence or collection relative to the others.
-
C.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
-
D.
firstToFeature
Indicates that one entity was the earliest or initial subject to exhibit, include, or present another entity in a given context.
-
E.
wasFirst
chosen
Indicates that one entity occurred, appeared, or held a position before another in time or sequence.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c1d8188190b15a641a08345adc |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.