Triple
T15957242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunisian Ligue Professionnelle 1 |
E386966
|
entity |
| Predicate | hasTeam |
P330
|
FINISHED |
| Object | AS Marsa |
E385743
|
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: AS Marsa | Statement: [Tunisian Ligue Professionnelle 1, hasTeam, AS Marsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AS Marsa Context triple: [Tunisian Ligue Professionnelle 1, hasTeam, AS Marsa]
-
A.
Marsa
Marsa is a town in Malta located on the shores of the Grand Harbour, known historically for its port and industrial facilities.
-
B.
La Marsa
chosen
La Marsa is a coastal suburb of Tunis in northern Tunisia, known for its beaches, upscale residential areas, and historic seaside charm.
-
C.
Marsan
Marsan is a small rural settlement located within the Qakh District of Azerbaijan.
-
D.
Masarra
Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
-
E.
Marsa al-Brega
Marsa al-Brega is a coastal industrial town in northeastern Libya known for its major oil refinery and petrochemical facilities on the Gulf of Sidra.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fc6f348190b49c4858281a0904 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe7e76d481909e6f1d1ea33edd60 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.