Triple
T17082157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autovía M-503 |
E414498
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
M-503
M-503 is a Spanish autovía (high-capacity road) in the Community of Madrid that connects several western suburbs with the capital’s main highway network.
|
E1250236
|
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: M-503 | Statement: [Autovía M-503, hasAbbreviation, M-503]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M-503 Context triple: [Autovía M-503, hasAbbreviation, M-503]
-
A.
M-501
M-501 is a major regional road in the Community of Madrid that connects Boadilla del Monte with other nearby municipalities and routes.
-
B.
M-506
M-506 is a regional road in the Community of Madrid, Spain, that serves as a key connector for the municipality of Pinto and surrounding areas.
-
C.
M-513
M-513 is a regional road in the Community of Madrid, Spain, that connects the town of Brunete with other nearby municipalities and major routes.
-
D.
M-50
M-50 is a state trunkline highway in Michigan that runs east–west across the southern part of the state, connecting several communities and major routes.
-
E.
M-50
M-50 is a major orbital motorway around Madrid, Spain, designed to divert traffic from the city center and connect key suburbs and highways.
- 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: M-503 Triple: [Autovía M-503, hasAbbreviation, M-503]
Generated description
M-503 is a Spanish autovía (high-capacity road) in the Community of Madrid that connects several western suburbs with the capital’s main highway network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M-503 Target entity description: M-503 is a Spanish autovía (high-capacity road) in the Community of Madrid that connects several western suburbs with the capital’s main highway network.
-
A.
M-501
M-501 is a major regional road in the Community of Madrid that connects Boadilla del Monte with other nearby municipalities and routes.
-
B.
M-506
M-506 is a regional road in the Community of Madrid, Spain, that serves as a key connector for the municipality of Pinto and surrounding areas.
-
C.
M-513
M-513 is a regional road in the Community of Madrid, Spain, that connects the town of Brunete with other nearby municipalities and major routes.
-
D.
M-50
M-50 is a major orbital motorway around Madrid, Spain, designed to divert traffic from the city center and connect key suburbs and highways.
-
E.
M-50
M-50 is a state trunkline highway in Michigan that runs east–west across the southern part of the state, connecting several communities and major routes.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe408d48190b4f52c2102eae7c2 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ee416c4819087e7ae0ead47867a |
completed | May 11, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_6a01323dd9188190981d6994a8d1a89e |
completed | May 11, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0136310e808190a0d350ae7f216d93 |
completed | May 11, 2026, 1:51 a.m. |
Created at: April 10, 2026, 5:34 a.m.