Triple
T37545129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babe Parilli |
E933442
|
entity |
| Predicate | touchdownPassesInAFL |
P17447
|
FINISHED |
| Object | over 150 |
—
|
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: over 150 | Statement: [Babe Parilli, touchdownPassesInAFL, over 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touchdownPassesInAFL Context triple: [Babe Parilli, touchdownPassesInAFL, over 150]
-
A.
AFLPassingTouchdownsLeader
Indicates that the subject is the player who led the AFL in passing touchdowns over a specified season or time period.
-
B.
NFLTouchdownPasses
Indicates that a player successfully throws a pass that results in a touchdown being scored in an NFL game.
-
C.
touchdownsScored
Indicates the number of touchdowns that an entity has scored.
-
D.
ledNFLInPassingTouchdowns
Indicates that the subject was the league leader in passing touchdowns in the NFL for a given season or time period.
-
E.
passingTouchdownsCareer
chosen
Indicates the total number of touchdown passes a player has thrown over the course of their entire 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.