Triple
T19005827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Matas railway station |
E465078
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Las Matas |
—
|
NE NERFINISHED |
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: Las Matas | Statement: [Las Matas railway station, locatedIn, Las Matas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Las Matas Context triple: [Las Matas railway station, locatedIn, Las Matas]
-
A.
Las Matas
chosen
Las Matas is a residential locality in the Community of Madrid, Spain, known as a suburban area closely linked to and bordering the municipality of Las Rozas de Madrid.
-
B.
Las Matas de Santa Cruz
Las Matas de Santa Cruz is a town in the Monte Cristi province of the Dominican Republic, known as the birthplace of MLB slugger Nelson Cruz.
-
C.
Loíza
Loíza is a coastal municipality in Puerto Rico known for its rich Afro-Puerto Rican culture, traditional Bomba music and dance, and vibrant religious and folk festivals.
-
D.
Rosarito
Rosarito is a coastal resort city in northern Baja California, Mexico, known for its beaches, tourism, and proximity to the U.S. border.
-
E.
Santa Mesa
Santa Mesa is a historic district in Manila, Philippines, known for its role as a key battleground during the early stages of the Philippine–American War.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a494688190a277b2cddf300235 |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:01 p.m.