Triple
T7653496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mordecai Brown |
E173317
|
entity |
| Predicate | handInjuryEffect |
P61582
|
FINISHED |
| Object | developed a highly effective curveball |
—
|
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: developed a highly effective curveball | Statement: [Mordecai Brown, handInjuryEffect, developed a highly effective curveball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handInjuryEffect Context triple: [Mordecai Brown, handInjuryEffect, developed a highly effective curveball]
-
A.
handednessAfterInjury
Indicates the dominant hand or handedness a person exhibits following an injury, especially in contrast to their prior handedness.
-
B.
handCondition
chosen
Indicates the state or quality of a hand, such as its health, functionality, or any specific condition affecting it.
-
C.
injuredBodyPart
Indicates that an entity has sustained an injury specifically affecting a particular body part.
-
D.
lostLimb
Indicates that an entity has had one or more of its limbs removed or rendered permanently absent, typically as a result of injury, surgery, or trauma.
-
E.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.