Triple
T17094161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T1 (Casablanca tramway) |
E414798
|
entity |
| Predicate | hasRouteDesignation |
P5539
|
FINISHED |
| Object | T1 |
E414798
|
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: T1 | Statement: [T1 (Casablanca tramway), hasRouteDesignation, T1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T1 Context triple: [T1 (Casablanca tramway), hasRouteDesignation, T1]
-
A.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
B.
T1
chosen
T1 is one of the main tram lines in Casablanca’s urban light rail network, providing mass transit service across key districts of the city.
-
C.
T1
T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
-
D.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
-
E.
T1
T1 is a major suburban rail service line in Sydney, Australia, forming part of the city's metropolitan train network.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfb89348190942984037bd3bd2e |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139fbcbc08190be2a96d03daf0384 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.