Triple
T15962669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Société des Transports de Tunis |
E387099
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Transtu |
E386961
|
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: Transtu | Statement: [Société des Transports de Tunis, alsoKnownAs, Transtu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Transtu Context triple: [Société des Transports de Tunis, alsoKnownAs, Transtu]
-
A.
Transtu
chosen
Transtu is the public transport authority in Tunis responsible for operating the city’s metro and other urban transit services.
-
B.
Trasop
Trasop is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its quiet streets and proximity to green areas.
-
C.
Tran
Tran is a personal name, commonly used as both a given name and surname in various cultures, particularly in East and Southeast Asia.
-
D.
Transy
Transy is the commonly used nickname for Transylvania University, a private liberal arts college in Lexington, Kentucky.
-
E.
Chantrans
Chantrans is a small commune in the Doubs department of eastern France, situated in the Bourgogne-Franche-Comté region.
- 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_69e157013cfc819099fa83de85273710 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3c3aae081909366c01b3fec4d47 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.