Triple
T24348671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marco Carducci |
E613720
|
entity |
| Predicate | playsPositionInSport |
P11645
|
FINISHED |
| Object | goalkeeper in soccer |
—
|
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: goalkeeper in soccer | Statement: [Marco Carducci, playsPositionInSport, goalkeeper in soccer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsPositionInSport Context triple: [Marco Carducci, playsPositionInSport, goalkeeper in soccer]
-
A.
playsInPosition
Indicates that an entity (typically a player) performs or operates in a specific role or position within a game, sport, or activity.
-
B.
playingPosition
chosen
Indicates the specific role or position an individual occupies while participating in a game or sport.
-
C.
typicalPlayingPosition
Indicates the usual role or position an entity regularly occupies when participating in a game, sport, or similar activity.
-
D.
positionPlayedForTeam
Indicates the specific playing position or role an individual held while participating on a particular team.
-
E.
coachPositionPlayed
Indicates the role or position a coach played (typically as a player) in the sport they are associated with.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293430524819087984a699d1d3687 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:58 a.m.