Triple
T17093708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Boraq |
E414786
|
entity |
| Predicate | rollingStock |
P1305
|
FINISHED |
| Object | Alstom Euroduplex |
E1249872
|
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: Alstom Euroduplex | Statement: [Al Boraq, rollingStock, Alstom Euroduplex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alstom Euroduplex Context triple: [Al Boraq, rollingStock, Alstom Euroduplex]
-
A.
Alstom Euroduplex
chosen
The Alstom Euroduplex is a high-speed, double-deck electric multiple unit train designed for long-distance services on advanced rail networks such as Morocco’s Al Boraq line.
-
B.
Alstom Metropolis
Alstom Metropolis is a family of modern, high-capacity metro trains manufactured by Alstom and used in urban rapid transit systems worldwide.
-
C.
Alstom Eurotram
The Alstom Eurotram is a distinctive low-floor light rail vehicle known for its sleek, modern design and panoramic windows, widely used on urban tram networks in Europe.
-
D.
Alstom Juniper
Alstom Juniper is a family of electric multiple unit trains built by Alstom for use on the British railway network.
-
E.
Siemens ACS-64
The Siemens ACS-64 is a high-speed, electric locomotive used by Amtrak for passenger rail service in the United States.
- 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_6a0139fa0a288190af69201ec88ec3c6 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.