Triple
T13143892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFE Trenes de Chile |
E312285
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Biotren |
E312286
|
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: Biotren | Statement: [EFE Trenes de Chile, hasSubsidiary, Biotren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biotren Context triple: [EFE Trenes de Chile, hasSubsidiary, Biotren]
-
A.
Biotrén
chosen
Biotrén is a suburban commuter rail system serving the Greater Concepción area in southern Chile.
-
B.
Biolon
Biolon is a tributary stream that feeds into Lake Annecy in southeastern France.
-
C.
Tetro
Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
-
D.
Sprantal
Sprantal is a village district of the town of Bretten in the state of Baden-Württemberg, Germany.
-
E.
Byetone
Byetone is a German electronic musician and visual artist known for his minimalist, experimental sound design and work with the Raster-Noton label.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bce3678819082a7aa1d83f20592 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5d809948190aced5ce377402463 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:10 p.m.