Triple
T11162069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Thibodeau |
E264059
|
entity |
| Predicate | teamDefensiveRanking |
P13143
|
FINISHED |
| Object | multiple top-5 NBA defenses |
—
|
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 top-5 NBA defenses | Statement: [Thomas Thibodeau, teamDefensiveRanking, multiple top-5 NBA defenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamDefensiveRanking Context triple: [Thomas Thibodeau, teamDefensiveRanking, multiple top-5 NBA defenses]
-
A.
defenseTeam
Indicates a relationship where one party serves as the legal defense representatives or advocates for another party in a legal or adversarial proceeding.
-
B.
defensiveRole
chosen
Indicates that an entity serves a protective or guarding function in relation to another entity or context.
-
C.
defensiveTackle
Indicates that an entity plays the defensive tackle position, typically lining up on the interior of the defensive line to disrupt offensive plays.
-
D.
opponentDefensiveLine
Indicates the defensive line formed by the opposing side in a competitive or adversarial context.
-
E.
allDefensiveFirstTeamPlayer
Indicates that the subject is a player who has been selected to an all-defensive first 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8832fe88190a74d81f9ed547baa |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.