Triple
T13143893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFE Trenes de Chile |
E312285
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Terrasur |
E1025047
|
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: Terrasur | Statement: [EFE Trenes de Chile, hasSubsidiary, Terrasur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terrasur Context triple: [EFE Trenes de Chile, hasSubsidiary, Terrasur]
-
A.
Terrasur
chosen
Terrasur is a Chilean intercity passenger rail service operated under the state-owned railway company Empresa de los Ferrocarriles del Estado (EFE).
-
B.
Terra Chã
Terra Chã is a civil parish on Terceira Island in the Azores, Portugal, forming part of the municipality of Angra do Heroísmo.
-
C.
Mapun
Mapun is an Austronesian language spoken primarily by the Mapun people of the southern Philippines, particularly on Mapun (Cagayan de Sulu) Island in the Sulu Sea.
-
D.
Terra do Sal
Terra do Sal is a nickname for Mossoró, a city in Brazil’s Rio Grande do Norte state known for its significant salt production.
-
E.
Terra da Garoa
Terra da Garoa is a popular nickname for the Brazilian metropolis of São Paulo, alluding to its characteristic light, misty rain.
- 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.