Triple
T4212781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Bay Packers–Detroit Lions rivalry |
E93943
|
entity |
| Predicate | franchiseRelocation |
P36297
|
FINISHED |
| Object | Portsmouth Spartans to Detroit Lions |
—
|
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: Portsmouth Spartans to Detroit Lions | Statement: [Green Bay Packers–Detroit Lions rivalry, franchiseRelocation, Portsmouth Spartans to Detroit Lions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: franchiseRelocation Context triple: [Green Bay Packers–Detroit Lions rivalry, franchiseRelocation, Portsmouth Spartans to Detroit Lions]
-
A.
teamRelocationTo
chosen
Indicates the movement of a team from one location to another as its new home or base of operations.
-
B.
movedHeadquartersFrom
Indicates that an entity relocated its main headquarters from one specified place to another.
-
C.
losingFranchise
Indicates that one entity ceases to hold or control a franchise previously granted to it by another entity.
-
D.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
-
E.
cityLosingFranchise
Indicates that a city is losing, or has lost, a professional sports franchise or major team based there.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.