Triple
T11815359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 3 |
E280985
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | T3 |
unclear NED1
|
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: T3 | Statement: [Terminal 3, alsoKnownAs, T3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T3 Context triple: [Terminal 3, alsoKnownAs, T3]
-
A.
T3
T3 is a tram line within the Casablanca Tramway network that serves as one of the city’s main urban light rail routes.
-
B.
T3
T3 is an American rapper best known as a founding member of the influential Detroit hip hop group Slum Village.
-
C.
T3
T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
-
D.
T3
T3 is one of the main lines of the Athens tram system, providing light rail service that connects key coastal and urban areas of the city.
-
E.
T3
T3 is a tram line in the Lyon public transport network in France, connecting the city center with eastern suburbs and key hubs like Part-Dieu station and the Eurexpo exhibition center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ccbbd481908c9013cb5a50c079 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131b62abc8190a02f584541baaee5 |
completed | April 28, 2026, 10:16 p.m. |
Created at: April 8, 2026, 9:42 p.m.