Triple
T32887956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Schultz |
E841251
|
entity |
| Predicate | plusMinusValue |
P175855
|
FINISHED |
| Object | +50 in 2009–10 NHL season |
—
|
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: +50 in 2009–10 NHL season | Statement: [Jeff Schultz, plusMinusValue, +50 in 2009–10 NHL season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plusMinusValue Context triple: [Jeff Schultz, plusMinusValue, +50 in 2009–10 NHL season]
-
A.
plusMinusLeader
Indicates the entity that leads others in net positive-minus-negative performance or score within a given context.
-
B.
positiveValueMeans
Indicates that a positive numerical value for a property or measure corresponds to the presence, increase, or affirmation of the associated condition or effect.
-
C.
oppositeNumber
Indicates that one number is the additive inverse of the other, such that their sum equals zero.
-
D.
addsValueBy
Indicates that one entity increases, enhances, or contributes positively to the worth, quality, or effectiveness of another entity.
-
E.
neutralValue
Indicates that the relationship or action has no positive or negative bias, effect, or preference toward any of the involved entities.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d749e7f081909c8196898c4191ad |
completed | May 3, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:18 a.m.