Triple
T5266217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roslagsbanan |
E118941
|
entity |
| Predicate | rollingStock |
P1305
|
FINISHED |
| Object |
X10p EMU
X10p EMU is a class of electric multiple unit trains used on Stockholm’s narrow-gauge Roslagsbanan commuter rail network.
|
E507454
|
NE FINISHED |
How this triple was built (4 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: X10p EMU | Statement: [Roslagsbanan, rollingStock, X10p EMU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: X10p EMU Context triple: [Roslagsbanan, rollingStock, X10p EMU]
-
A.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
B.
X60 EMU
The X60 EMU is a modern electric multiple unit train used for high-capacity commuter services in the Stockholm region.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
E.
Z 8800 EMU
The Z 8800 EMU is a class of French electric multiple unit trains operated by SNCF, primarily used for suburban commuter services in the Paris region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: X10p EMU Triple: [Roslagsbanan, rollingStock, X10p EMU]
Generated description
X10p EMU is a class of electric multiple unit trains used on Stockholm’s narrow-gauge Roslagsbanan commuter rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: X10p EMU Target entity description: X10p EMU is a class of electric multiple unit trains used on Stockholm’s narrow-gauge Roslagsbanan commuter rail network.
-
A.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
B.
X60 EMU
The X60 EMU is a modern electric multiple unit train used for high-capacity commuter services in the Stockholm region.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
E.
Z 8800 EMU
The Z 8800 EMU is a class of French electric multiple unit trains operated by SNCF, primarily used for suburban commuter services in the Paris region.
- F. None of above. chosen
Provenance (5 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bfabf9c819098f961243c31e508 |
completed | March 20, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe8e5c948190a807a99bd35f710d |
completed | March 21, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69beff3029dc8190b4dc5e207a2bfa03 |
completed | March 21, 2026, 8:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69befffc0e388190a02624d4f466a2a9 |
completed | March 21, 2026, 8:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.