Triple
T16213011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrell Suggs |
E393512
|
entity |
| Predicate | careerSacksOver |
P41411
|
FINISHED |
| Object | 130 |
—
|
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: 130 | Statement: [Terrell Suggs, careerSacksOver, 130]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerSacksOver Context triple: [Terrell Suggs, careerSacksOver, 130]
-
A.
careerSacks
chosen
Indicates the total number of times a defensive player has sacked a quarterback over the course of their entire career.
-
B.
careerReceptions
Indicates the total number of receptions a player has made over the course of their entire career.
-
C.
careerSteals
Indicates the total number of steals a player has accumulated over their entire career.
-
D.
careerOPS
Indicates a relationship where an entity’s career on-base plus slugging (OPS) statistic is recorded or associated with that entity.
-
E.
careerStrikeouts
Indicates the total number of batters a pitcher has struck out over the course of their entire professional career.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f2c1288190bfaed49c364bfa22 |
completed | April 17, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.