Triple
T22937882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lance Dwight Alworth |
E569634
|
entity |
| Predicate | statisticReceivingYards |
P10746
|
FINISHED |
| Object | 10966 |
—
|
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: 10966 | Statement: [Lance Dwight Alworth, statisticReceivingYards, 10966]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statisticReceivingYards Context triple: [Lance Dwight Alworth, statisticReceivingYards, 10966]
-
A.
careerReceivingYards
chosen
Indicates the total number of yards a player has gained by receiving the ball over the course of their entire career.
-
B.
singleSeasonReceivingYards
Indicates the total number of receiving yards a player gains during a single season.
-
C.
singleSeasonReceivingYardsSeason
Indicates the total number of receiving yards a player gained in a single football season.
-
D.
ledLeagueInReceivingYards
Indicates that the subject had the highest total receiving yards in the league for a given season or time period.
-
E.
sportNumberOfReceptionsNFL
Indicates the number of receptions a player has made in NFL games.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18136bf448190afa04f8b55a8bb6e |
completed | April 29, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.