Triple
T12303224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestra Italia |
E293283
|
entity |
| Predicate | successorSport |
P104348
|
FINISHED |
| Object | football |
—
|
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: football | Statement: [Palestra Italia, successorSport, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorSport Context triple: [Palestra Italia, successorSport, football]
-
A.
successorManufacturer
Indicates that one manufacturer has taken over, replaced, or continued the role or operations of another manufacturer as its successor.
-
B.
successorCompetition
Indicates that one competition directly follows another in sequence, serving as its successor in a series or timeline.
-
C.
successorSeries
Indicates that one series directly follows another in sequence, continuing or extending it as its successor.
-
D.
successor
Indicates that one entity directly follows another in an ordered sequence or position.
-
E.
successorInMarket
Indicates that one entity has taken over or followed another in serving the same market or customer base.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:53 p.m.