Triple
T5239409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derrick Thomas |
E118301
|
entity |
| Predicate | allProSelectionsSecondTeam |
P59080
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Derrick Thomas, allProSelectionsSecondTeam, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allProSelectionsSecondTeam Context triple: [Derrick Thomas, allProSelectionsSecondTeam, 4]
-
A.
allProSecondTeamSelectionCount
chosen
Indicates the number of times an entity has been selected to the All-Pro Second Team.
-
B.
NBAAllNBASecondTeamSelections
Indicates the number of times an entity has been selected to the NBA All-NBA Second Team.
-
C.
nflAllProSelection
Indicates that a player was selected to an NFL All-Pro team for a given season or time period.
-
D.
allProSelectionCount
Indicates the number of times an entity has been selected for an All-Pro team or equivalent top-level professional recognition.
-
E.
NBAAllDefensiveSecondTeamSelections
Indicates the number of times an entity has been selected to the NBA All-Defensive Second Team.
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b290b88819095bc99c234260d25 |
completed | March 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69bd77c1397c8190a7fd844d7a396e54 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:49 p.m.