Triple
T7095214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xavier Thames |
E165306
|
entity |
| Predicate | collegeTeamNumberOfSeasons |
P74510
|
FINISHED |
| Object | multiple seasons with San Diego State Aztecs |
—
|
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: multiple seasons with San Diego State Aztecs | Statement: [Xavier Thames, collegeTeamNumberOfSeasons, multiple seasons with San Diego State Aztecs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeTeamNumberOfSeasons Context triple: [Xavier Thames, collegeTeamNumberOfSeasons, multiple seasons with San Diego State Aztecs]
-
A.
numberOfSeasonsWithTeam
Indicates the total count of seasons an entity (e.g., a player or coach) has spent with a particular team.
-
B.
yearsWithTeam
Indicates the number of years an entity (typically a person) has been associated with or part of a particular team.
-
C.
collegeTeamChampionships
Indicates the championships or titles that a college sports team has won.
-
D.
collegeTeam
Indicates that one entity is a sports team that represents or is affiliated with a particular college or university.
-
E.
collegeTeamNumber
Indicates the identifying number assigned to a college sports team.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5530f2081908ac969ddfa7e9b5a |
completed | March 27, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c172148190bf290c07bf579d1f |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e24af9ac8190b24eee206ba8be36 |
completed | March 27, 2026, 8:02 p.m. |
Created at: March 27, 2026, 2:41 p.m.