Triple
T12382018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Essien |
E295766
|
entity |
| Predicate | league |
P888
|
FINISHED |
| Object | Ligue 1 |
E66666
|
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: Ligue 1 | Statement: [Michael Essien, league, Ligue 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ligue 1 Context triple: [Michael Essien, league, Ligue 1]
-
A.
Ligue 1
chosen
Ligue 1 is France’s top professional football division, featuring the country’s leading clubs in the highest tier of its league system.
-
B.
Ligue 1 and Ligue 2
Ligue 1 and Ligue 2 are the top two professional divisions of French football, forming the elite tiers of the national league system.
-
C.
Ligue A (France)
Ligue A (France) is the top professional men's volleyball league in France, featuring the country's leading clubs in the sport.
-
D.
Ligue de Football Professionnel
The Ligue de Football Professionnel is the organization that oversees and manages France’s top professional football leagues and related competitions.
-
E.
Ligue 2
Ligue 2 is the second tier of professional football in the French league system, sitting directly below Ligue 1.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ab066108190bba8eca95d3e0a81 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:54 p.m.