Triple
T11713957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Edward Kelly |
E278443
|
entity |
| Predicate | careerPassingTouchdownsNFL |
P100924
|
FINISHED |
| Object | 237 |
—
|
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: 237 | Statement: [James Edward Kelly, careerPassingTouchdownsNFL, 237]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerPassingTouchdownsNFL Context triple: [James Edward Kelly, careerPassingTouchdownsNFL, 237]
-
A.
careerReceivingTouchdowns
Indicates the total number of touchdowns a player has scored by receiving the ball over the course of their entire career.
-
B.
careerNFLTouchdowns
Indicates the total number of touchdowns a player has scored over the course of their NFL career.
-
C.
careerRushingTouchdowns
Indicates the total number of rushing touchdowns a player has scored over the entire span of their career.
-
D.
careerTotalTouchdowns
Indicates the total number of touchdowns an entity has scored over the entire duration of its career.
-
E.
ledNFLInPassingTouchdowns
Indicates that the subject was the league leader in passing touchdowns in the NFL for a given season or time period.
- F. None of above. chosen
Provenance (4 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4bf54d88190a8e07fbbf8d9e962 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:40 p.m.