Triple
T2507583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tip and Tap |
E52619
|
entity |
| Predicate | governingBody |
P46
|
FINISHED |
| Object | FIFA |
E23480
|
NE 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: FIFA | Statement: [Tip and Tap, governingBody, FIFA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FIFA Context triple: [Tip and Tap, governingBody, FIFA]
-
A.
FIFA
chosen
FIFA is the international governing body of association football, responsible for organizing major global tournaments such as the FIFA World Cup and overseeing the sport’s rules and international governance.
-
B.
PES
PES is a major European political party that unites social-democratic, socialist, and labor parties from across the European Union.
-
C.
EA Sports
EA Sports is a video game brand of Electronic Arts best known for developing popular sports game franchises such as FIFA (now EA Sports FC) and Madden NFL.
-
D.
NBA 2K
NBA 2K is a long-running basketball video game series that simulates the NBA with realistic gameplay, teams, and players.
-
E.
Sega Sports
Sega Sports was Sega's sports-focused publishing label known for producing and releasing popular sports video game franchises in the late 1990s and early 2000s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1faa33148190a3ad6ece7432b81f |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.