Triple
T14629330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Immaculate Reception |
E343437
|
entity |
| Predicate | yardsToFirstDown |
P34478
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Immaculate Reception, yardsToFirstDown, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yardsToFirstDown Context triple: [Immaculate Reception, yardsToFirstDown, 10]
-
A.
ledLeagueInYardsFromScrimmage
Indicates that the subject achieved the highest total yards gained from scrimmage in the league for a given season or period.
-
B.
touchdownPoints
Indicates the number of points awarded to a team for successfully scoring a touchdown in a game.
-
C.
yardsPerReception
Indicates the average number of yards gained each time a player makes a reception.
-
D.
hasYardage
chosen
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
E.
yardsFromScrimmageCareerNFL
Indicates the total number of yards a player has gained from scrimmage over their entire NFL 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a7c8fc81909d10c1f563d7d1e7 |
completed | April 14, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.